ENVIRONMENTAL STUDIES, SOUTH TEXAS OUTER CONTINENTAL SHELF, 1975-1977 VOLUME I ECOSYSTEM DESCRIPTION edited by: R. Warren Flint Nancy N. Rabalais submitted to: The Bureau of Land Management Washington, D.C. Contract AASSI-CTB-51 by: The University of Texas Marine Science Institute Port Aransas Marine Laboratory Port Aransas, Texas 78373 January 1980 „ This report has been reviewed by the Bureau of Land Manage­ ment and approved for publication. Mention of trade names or commercial products does not constitute endorsement; or: recommendation for use. II S. K. Alexander, Moody College of Marine Sciences, Texas A&M University, Galveston, Texas 77550 E. W. Behrens, University of Texas Marine Science Institute, Geophysical Laboratory, Galveston, 77550 Texas R. A. Benavides, University of Texas Marine Science Institute, Port Aransas Marine Laboratory, Port Aransas, Texas 78373 B. B. Bernard, Texas A&M University, Department of Oceanography, College Station, Texas 77843 P. N. Boothe, Texas A&M University, Department of Oceanography, College Station, Texas 77843 J. M. Brooks, Texas A&M University, Department of Oceanography, College Station, Texas 77843 R. W, Flint, University of Texas Marine Science Institute, Port Aransas Marine Laboratory, Port Aransas, Texas 78373 S. C. Giam, Texas A&M University, Department of Chemistry, College Station, Texas 77843 R. C. Godbout, University of Texas Marine Science Institute, Port Aransas Texas Marine Laboratory, Port Aransas, 78373 W. C. Griffin, University of Texas Marine Science Institute, Port Aransas Marine Laboratory, Port Aransas, Texas 78373 J. S. Holland, University of Texas Marine Science Institute, Port Aransas Marine Laboratory, Port Aransas, Texas 78373 D. L, Kamykowski, North Carolina State University, Department of Marine Sciences and Envineering, Raleigh, North Carolina 27650 D. S. Milton, University of Texas Marine Science Institute, Port Aransas Marine Laboratory, Port Aransas, Texas 78373 J. D. McEachran, Texas A&M University, Department of Wildlife and Fisheries Sciences, College Station, Texas 77843 G. S. Texas A&M Neff, University, Department of Chemistry, College Station, Texas 77843 E. T, Park, Moody College of Marine Sciences, Texas A&M University, Galveston, Texas 77550 P. L. Parker, University of Texas Marine Science Institute, Port Aransas Marine Laboratory, Port Aransas, Texas 78373 L. H. Pequegnat, Texas A&M University, Department of Oceanography, College Station, Texas 77843 W. E. Pequegnat, Texas A&M University, Department of Oceanography, College Station, Texas 77843 E. P. Powell, University of Texas, Department of Microbiology, Austin, Texas 78712 B. J. Presley, Texas A&M University, Department of Oceanography, College Station, Texas 77843 N. N. Rabalais, University of Texas Marine Science Institute, Port Aransas Marine Laboratory, Port Aransas, Texas 78373 R. M. Rogers, Contracting Officer’s Bureau of Authorized Representative, Land Management, Hale Boggs Federal Building, Suite 841, New Orleans, Louisiana 70130 R. S, Scalan, University of Texas Marine Science Institute, Port Aransas Marine Laboratory, Port Aransas, Texas 78373 J. R. Schwarz, Moody College of Marine Sciences, Texas A&M University, Galveston, Texas 77550 III N. P. Smith, Harbor Branch Foundation, Route 1 Box 196, Fort Pierce, Florida 33450 P. J. Szaniszlo, University of Texas, Department of Microbiology, Austin, Texas 78712 P. E. Turk, Moody College of Marine Sciences, Texas A&M University, Galveston, Texas 77550 C. Texas Venn, A&M University, Department of Oceanography, College Station, Texas 77843 J. K. Winters, University of Texas Marine Science Institute, Port Aransas Marine Laboratory, Port Aransas, Texas 78373 D. E. Wohlschlag, University of Texas Marine Science Institute, Port Aransas Marine Laboratory, Port Aransas, Texas 78373 J. Texas A&M H. Wormuth, University, Deparment of Oceanography, College Station, Texas 77843 R. M. Yoshiyama, University of Texas Marine Science Institute, Port Aransas Marine Laboratory, Port Aransas, Texas 78373 IV To Debby Kalke without whose persistence and diligence throughout years of this program the we could not '’nave arrived at a successful completion. A personal from all of us. thanks V FOREWORD This study of the south Texas outer continental shelf (STOCS) was conducted on behalf of the U. S. Bureau of Land Management and with the close cooperation of personnel of that agency. The studies reported on herein constituted the fourth year of an environmental studies program of the STOCS. This study was part of an overall program that included the other elements of 1) geology and geophysics by the U. S. Geological fisheries Survey, 2) resources and ichthyoplankton populations by the National Oceanic and Atmospheric Administration/National Marine Fisheries Service, and 3) biological and chemical characteristics of selected topo­graphic features in the northern Gulf of Mexico by Texas A&M University, The resultant data from this investigation represent the first petroleum exploration and development in the STOCS area. The central goal of these and other environmental quality surveys of continental shelf areas is the protection of the living marine resources from deleterious effects. This investigation was the result of the combined efforts of scien­tists and support personnel from several universities. The hard work and cooperation of all participants is gratefully acknowledged. VI TABLE OF CONTENTS Page Preface ix Contents Volume II Contents Volume 111 xiii VOLUME I Executive Summary x^v Chapter 1 Introduction 1 Background Study Area Program Description Program Management 1 7 10 13 Chapter 2 Marine Pelagic Environment 17 Marine Meteorology Physical Oceanography Water Chemistry Nutrients Hydrocarbons;High-Molecular-Weight Molecular-Weight and Low­ 17 21 40 Chapter 3 Pelagic Biota 47 Phytoplankton Nepheloid Layer Neuston Zooplankton Zooplankton Body Hydrocarbons Trace Metals Burdens 47 59 31 39 75 75 79 Chapter 4 Marine Benthic Environment 33 General Features Sediment Structure Sediment Chemistry 33 34 91 Chapter 5 Benthic Biota 103 Microbiology Marine Fungi Marine Bacteria Meiofauna 104 104 HO H5 VII Page Macrofauna 123 Infauna 123 Epifauna 139 Demersal Fish 149 Biota Body Burdens 180 Hydrocarbons 180 171 Trace Metals 177 6 Chapter Ecosystem Characteristics ' 177 Nutrient Regeneration 180 Trophic Coupling 184 200 General Trends Environmental Disturbance 205 References A Baseline Results: Distributional Characteristics of Selected Variables Appendix A-l Appendix B Variable Geographic Distributional Mapping B-l VIII PREFACE The present concern about the rate of fossil-fuel consumption and dependency upon import oil to supply current U. S. demands has resulted in a greater focus of interest by both the U. S. government and oil com­ panies on the U. S. continental shelf for increased domestic production. The 1969 National Environmental Policy Act (NEPA) identifies the U. S. Department of the Interior as the responsible agency for protecting the of marine environment of the continental shelf during periods exploration and exploitation of natural resources. To obtain information upon which to base decisions concerning the orderly development of these resources while also protecting the environment, the Bureau of Land Management (BLM), an agency of the Department of the Interior, established a marine environ­ mental studies program for the outer continental shelf. This document is a of the results of three years of field presentation studies and data collection on the south Texas outer continental shelf, one of the BLM programs, integrating the information obtained into a statement of the ecosystem characteristics of this shelf area. The intent of the contributions contained within this document is to provide the initial information needed by the environmental in order to make managers sound decisions concerning natural resource exploitation in these shelf waters. Besides a general ecosystem description presentation, an attempt has been made in this document to present, in a meaningful fashion, those relationships that exist in this environment and those specific character­ istics (variables) of this environment which are most important for pre­ diction, assessment and management of impacts to the south Texas outer continental shelf ecosystem. IX On 3 June while this document was a well blow­ 1979, in preparation, out occurred at the IXTOC off the I drilling site in the Bay of Campeche Mexican coast in the southwestern Gulf of Mexico. The events that followed this major disturbance to the marine environment of the Gulf, as the mas­ sive oil slicks entered U. S. waters, emphasized the value of this study program with its establishment of baseline conditions and ecosystem char­ acteristics. Through the information presented in the following volumes, federal agencies associated with the National Oil Spill Response Team that monitored the IXTOC I spill and developed a damage assessment plan of research were able to identify critical components of the shelf environment be used from and important variables that could to detect ecosystem change the spill impact. It is only hoped that the reasons for conducting the south Texas outer continental shelf research program will not be forgotten. Now that the opportunity exists to evaluate the actual impact of a major perturbation related to natural resource exploitation, decision-makers need to take full advantage of the extensive data base available to fill out numerous information gaps so that future decisions involving any shelf environment and resource exploitation can be made without a feeling of apprehension and uncertainty. Special acknowledgement is given to the scientists who served as previous Program Managers for the research program detailed in the follow- These include Robert S. Jones, Robert D. Groover, and Connie ing pages. R. Arnold. Acknowledgment is also given to Richard Casey, Jerry Neff, William Haensly, Particia Johansen, Chase Van Baalen, Samuel Ramirez, Helen Oujesky, William Van Auken, and Neal Guntzel for their overall scientific contributions to the South Texas Outer Continental Shelf Program even though they did not participate in the data synthesis aspect. We X their guidance during this program. R. Warren Flint Program Manager South Texas Outer Continental Shelf Environmental Studies University of Texas Marine Science Institute Port Aransas Marine Laboratory Port Aransas, Texas XI CONTENTS VOLUME II DATA MANAGEMENT Preface Chapter 1 Introduction Purpose and Function Personnel Structure Facilities Structure-Computer Facilities Overview Chapter 2 Data File Construction Inventory and Control Data Coding Sample Code Data File Maintenance Error Detection Chapter 3 Data Base File Organization General Aspects Data File Coding Construction fo Statistical Analysis Files Data Archiving Chapter 4 Statistical Analysis Strategies General Aspects Sampling Scheme Biological Patterns Data Reduction - Analysis of Individual Variables Distributional Characteristics Analysis for Spatial-Temporal Variation Variables Interrelationships Among Bivariate Correlation Analysis Multiple Regression Analysis for Bivariate Curvilinear Trends Multiple Discriminant Analysis Multiple Regression Analysis for Multivariate Relationships Fitting of Nonlinear Functions Appendix A-Data Base File Documentation XII XIII CONTENTS VOLUME 111 STUDY ELEMENT REPORTS Chapter 1 Introduction Chapter 2 Hydrography Chapter 3 Low-Molecular-Weight Hydrocarbons Chapter 4 High-Molecular-Weight Hydrocarbons in Water, Sediment, and Zooplankton Chapter 5 High-Molecular-Weight Hydrocarbons in Benthic Macroepifauna and Macronekton Chapter 6 Trace Metals in Zooplankton, Shrimp and Fish Chapter 7 Phytoplankton and Productivity Chapter 8 Analysis of a Two Year Study of Neuston Chapter 9 Zooplankton Chapter 10 Benthic Mycology Chapter 11 Analysis of Benthic Bacteria Chapter 12 Meiofauna Chapter 13 Benthic Invertebrates: Macroinfauna and Epifauna Chapter 14 Demersal Fishes N. N. Rabalais University of Texas Marine Science Institute Port Aransas Texas 3y The broad continental shelf of south Texas supports valuable commer­ cial and sport fisheries, particularly for penaeid shrimp, along with potential sites for exploration and exploitation of oil and gas resources. An intensive, multidisciplinary three-year study (1975-1977) to character­ ize the temporal and spatial variation of both the living and non-living resources of the area was designed to provide the initial information needed by environmental managers to make sound decisions concerning natural resource exploitation. The synthesis and integration of these data resulted in an encompassing description of the physical, chemical and biological and that components of the system, identifying the temporal spatial trends for best represented the ecosystem along with mathematical descriptions unique relationships that would serve as "fingerprints" for future compar­ or isons against which subsequent changes impacts could be compared, par­ ticularly in the light of oil and gas development activities. The study included the pelagic environment with its physical characterization, biotic composition and productivity; the benthic habitat physical setting and biotic composition; and inherent natural petroleum hydrocarbon and trace metal levels in selected portions of the physical and biological both pelagic and benthic. components, As research priorities were reassessed and additional information to meet determined necessary, the study was amended appropriately evolving study objectives. Sampling schemes varied from year to year and according to particular components of the overall study. In general the study area was traversed by four transects perpendicular to shore, each with six to XIV sampled varied with year, study element, and collection period. Samples were taken seasonally along all four transects during all three years. Monthly sampling was conducted on Transect II during 1976. Additional sites included stations near two hard bottom features, Hospital Rock and Southern Bank, and an exploratory drilling rig monitoring study site. The resultant large and encompassing data base was synthesized and inte­ grated to describe characteristics and interactions of the physical, chem­ ical and biological components of the south Texas continental shelf. A summarization of the highlights of this study follows. The Texas shelf environment is a complex interaction of adjacent land masses, nearshore coastal waters influenced by estuarine systems and their inherent high productivity, riverine input in particular from the Mississippi River, and dynamics of open Gulf waters. The climate of south Texas is subtropical and dry, subhumid with an average yearly rain­ fall of 70 cm. Because of semiarid conditions, not only along the coast but landward for more than a hundred miles, no major streams flow to the Gulf of Mexico along the coast between Aransas Pass Inlet and the Rio Grande, 125 miles to the south. The general circulation of air near the Gulf surface over coastal region follows the of the the south Texas sweep western extension of the Bermuda high pressure system throughout the year. a Relatively high surface water temperatures of the Gulf bring about great warming and increase in moisture content of the overlying air masses. Water mass distribution in open Gulf waters result from the inflow through the Yucatan Channel, outflow through the Straits of Florida, surface con­ ditions by local air-sea exchange processes and internal mixing of three well-defined water masses including Gulf basin water, a layer of Antarctic intermediate water, and a mid-Atlantic element. Thy hydrography is a XV resultant biological communities, which are a reflection of it. In surface water layers from 10 to 100 m across the south Texas shelf there is a cross shelf that strong temperature gradient during mid-winter disappears with seasonal heating until the surface water is spatially iso­ thermal at 29°C by late summer. The winter gradient produces lowest values of 14°C over the inner shelf and minimum values of 19 to 20°C over the outer shelf. Vertical stratification, nearly absent in shelf waters during the winter, is well-developed in the summer, being more prevalent with depth. Shelf salinities are high most of the year, a short except during period in spring and early summer, when a plume of Mississippi River water may cover the entire shelf, lowering salinities through the uppermost 20 to 30 m. There is suggestion of occasional upwelling of deep Gulf water at sites deeper than 100 m. An aspect of prime importance, particularly to the pelagic biological communities and the benthos, is the extreme variability of shallow waters and contrasting stability of deeper waters with both water temperature and salinity. At the shallower stations, salinity is almost totally influenced by local rainfall and riverine input. Also affecting shelf waters annually is a plume of Mississippi River water moving westward and southwestward along the northern rim of the Gulf of Mexico during spring and winter. This plume is especially the coast but at times the entire shelf. The covers pronounced along shelf is thus divided into three zones; 1) an inshore zone dominated by Texas riverine inputs, 2) a middle zone in which both Texas freshwater sources and the Mississippi River are influential with a gradation from to the other with increased distance offshore, and 3) an offshore one zone dominated by Mississippi River discharge. XVI dominates for the majority of the year (October through March) toward the southwest and is responsible for advective transport of Mississippi River waters along the northwestern rim of the Gulf of Mexico at a time when com- discharge is the greatest. Between June and September the longshore ponent is weaker and reverses over short time scales to periodically produce perpendicular movements of water across the shelf. Nearshore sur­ face currents are influenced by local prevailing winds. These water movements influence the transport of nutrients, heat, suspended solids, and planktonic life. The preceding description of hydrographic variables helps suggest some of the possible factors influencing the biotic compo­ nents of the pelagic system. Study of the pelagic biota shows that Texas shelf waters are extremely high in annual phytoplankton productivity. Primary production in inner- shelf waters is bimodal annually with peaks in spring and fall. There is a cross-shelf gradient of chlorophyll a_ concentrations with a peak inshore and a steep drop to offshore. Although not as strong, there is also a north-south gradient for chlorophyll a. on the shelf. The northern part of the shelf is higher in chlorophyll a_ at the surface and half the depth of the photic zone than the southern part. There is no north-south gra­ dient of chlorophyll a in the bottom waters, indicating a lack of mixing on the outer shelf. The higher concentrations of chlorophyll a are often in the bottom waters, especially at shallow stations characterized by a pervasive nepheloid layer. In this layer, peak chlorophyll levels (primary producer biomass), adequate light transmittance, and evidence of nutrient regeneration leads to occurrence of photosynthesis in bottom waters. XVII a reflection of different water masses on the shelf over annual cycles with temporal changes in community structure related to light intensity, day length, temperature, salinity, stratification, wind, and nutrient sources. Geographical trends in the phytoplankton are usually related to water depth or distance from shore with the highest abundances along the inner shelf. High spring phytoplankton numbers are correlated with river­ ine inputs and nutrient maxima. Neuston, the biota living on or just beneath the surface film of marine water, varies considerably in abundance, either as total numbers or dry weight, as well as taxonomic composition. Part of the variability is a result of diel vertical migration; the remainder, a reflection of envi­ ronmental heterogeneity. Cross-shelf variation in the distribution of some taxa, particularly the larval decapod crustaceans, occurs annually and is related to benthic distribution patterns of adults as well as estuarine influences. Neuston is significantly correlatedwith the amount of micro-tarballs. This relationship may be accounted for either from windrowing effects of surface water circulation or by the potential food source of epibiotic species associated with the well-weathered tarballs. Zooplankton biomass and total density decrease with distance offshore A few species, primarily female copepods, dominate the zooplankton density. There is considerable transect to transect variability suggesting the occurrence of pulsing inputs to the system which encourage zooplankton production but which are so limited that the entire length of the study area is not uniformly affected. The patchy distribution of zooplankton may be related to low salinity input Evidence for from bay systems. estuarine influence is the increased numbers of Aoartia tonsa a calanoid , copepod abundant in bays and estuaries of the Gulf of Mexico in the spring XVIII half of the study area. Salinity is related to several zooplankton vari­ ables at the shallow stations, but more frequently correlates with zoo- plankton variation at mid-depth stations. The implied relationships between zooplankton variables and salinity at the mid-depth stations may indirectly reflect a response of the zooplankton to changes in primary production which has been shown to be commonly associated with salinity changes in neritic waters. The direct relationship of zooplankton to phytoplankton at the deep stations reflects a close dependence of zoo- plankton on phytoplankton. The offshore zooplankton population may be controlled by food availability, while nearshore zooplankton populations may be controlled by predation. The general feature of the sea bottom is a broad ramp-like indenta­ tion on the outer shelf between two ancestral deltaic bulges, the Colorado Brazos in the north seaward of Matagorda Bay and the Rio Grande in the south. The sea floor is characterized by sand-sized sediments on the inner shelf which decrease in abundance seaward. Sand is transported seaward from the high energy zone of the innermost shelf. The encroach­ ment of sand particles onto the Texas shelf from the north suggests a regional southward movement of sediment. Within the study area at the deepest stations on all transects (106 to 134 m), sediments are characterized by silty (30%) clay of very uniform texture with occasional coarsening by winnowing of finest clays during the early spring. A slightly coarser, more variable silty clay is associated with stations in the northern three transects between 65 and 100 m water depth. These are transition stations between deeper clayey sediments and sediments of between 36 and 49 the silty m in the northern part of the study area, and farther landward (18 22 in the northern half and to m XIX to 37 m in the southern half) are the most variable inner-shelf sandy muds. A similar group of stations with greater variability, at least partly because of coarse sand with some gravel, are located between 47 and 91 mon the Rio Grande delta. Two stations, 4/1 and 1/IV, are charac­ terized by moderately variable muddy sands near the barrier shoreface sand- offshore mud boundary, whereas two others, 4/111 and 4/IV, are within the shoreface sands where variability is as low as the outermost stations due to efficiency of wave action constantly sorting the bottom sediments. At the inner-shelf stations, there is also a suggestion of seasonal coarsen­ ing in early spring with year-long coarsening that occurred in 1977, perhaps related to hurricane generated waves between spring and fall. One of the major focuses of this multidisciplinary study was charac­ terization of the subtidal benthic habitat. Unlike the water masses and associated biota which are in continual motion, the benthos is relatively stationary and thus serves as a barometer reflecting changes that occur in localized areas. Natural variations in the benthos occur in localized areas. Natural variation in the benthos and/or the transfer of materials through the community is important in understanding the essential links in the trophic dynamics of the Gulf of Mexico. The benthic community was studied by components determined categorically by taxa, size fraction, or relative position in the benthos and included microbiology, both fungal and bacterial; organisms living in the sediments, both the meiofauna (< 0,5 mm) and the macrofauna (> 0.5 mm); and those living above the sediments but closely associated with it, the invertebrate epifauna and the demersal fishes. in Marine fungi are present in benthic sediments with low numbers to fall. The the late winter significantly increasing through the year XX on lum from the water column seasonally which in turn depends deposition in the water column from continental air masses and by the availability of organic carbon locally. Fungi are short-lived in sediments where available carbon is a limiting factor. The pattern of increasing numbers an increase in numbers of taxa. Over 50% of the benthic is paralleled by of assimilating crude oil to overcome carbon limitations fungi are capable decreases offshore. It is reasonable to presume Oil degradation potential occur in the at least some fungal oxidation of intrusive petroleum would area. Marine aerobic heterotrophic bacteria are found in sediments in numbers from 4.6 x lO 4 to 1.3 x 10 s per ml wet sediment. Highest numbers are present during spring and lowest during winter. Highest populations the nearshore stations and decrease with depth offshore.occur at Benthic with the bacteria appear to increase high input of organic carbon to the sediments during periods of peak productivity in the overlying water column in spring and decrease with lower sediment temperatures in winter. Hydrocarbon degrading bacteria are present in sediments throughout the area and are also more numerous nearshore with decreasing numbers off­ shore. They are significantly correlated with the total alkanes in the sediments. Benthic bacteria are capable of degrading all n-alkanes (Cl to C32) but exhibit a preference for lower-molecular-weight hydrocar­ bons (Cm to C 2 0)• Stimulation of total anaerobic heterotrophic bacteria and hydrocarbon degrading bacteria by the addition of crude oil to the sediment occurs at the majority of stations examined. The meiofauna are those organisms smaller than 0.5 mm but larger than 0.1 mm. This is a somewhat arbitrary size definition to distinguish XXI these small metazoans from the larger macrofauna of the benthos. Further delineation to exclude the young of the macrofauna and include only spe­ cies which even at the adult stage fit into the stated size and fit certain taxonomic categories (i.e. the permanent meiobenthos) provides a more operational definition in terms of sampling methods and a natural grouping with certain biological characteristics. This definition differs from that of macrofauna in respect to reproductive capacity and general metab­ olism, as well as the ecological niche the meiofauna fill. Meiofaunal populations diminish with increasing depth on the Texas shelf. Consis­ tently Transect IV supports the highest populations inshore and Transect of the II the lowest. Populations deepest station of Transect II are almost as great as those of the shallowest station. In contrast, for the other three transects, populations at the deepest stations are only a small percentage of those of the shallowest stations. Nematodes are the most abundant meiofaunal taxa, averaging 93% of the total abundance of the permanent meiofauna. There is a marked increase in nematodes when the sand content of the sediment is 60% or more by weight. The macroinvertebrate infauna groups into stations similar to the groupings derived from sediment data. Community variables exhibit trends consistent with these groupings. The number of species is highest at shallow stations with a significant drop for the mid-depth group. Density is also greatest for the shallow sites with decreases in deeper waters on the shelf. These variables result in high species diversity measures for shallow stations. The highest diversity, however, is seen at the three stations on Transect IV mentioned earlier. The shallow stations are characterized by a few dominant fauna in contrast to the more evenly distributed populations offshore. Specific faunal assemblages describe the station groups. The species groups are represented by shallow XXII dominant faunal group'throughout the shelf. Analysis of physical variables associated with the benthos station indicates that there environmental differences between them. groups are Water depth is the dominant variable accounting for benthic community groupings on the shelf. Additionally, the sediment properties of sand/mud ratio, sediment grain size deviation, and percent silt account for varia­ tion between station groups. Factors related to water depth, the degree of food availability to the benthos and bottom water variability along the depth gradient, must also be considered. Chlorophyll a_ concentrations are highest and also most variable in shallow waters where highest densities of infauna occur. Lower concentrations of primary producers with less variable abundances in the deeper stations are associated with lowered densities of infauna and more evenly distributed population numbers within are these assemblages. Temperature and salinity also most variable at shallower depths with decreasing variability with increasing water depth. The shallow benthic habitat is more variable and less predictable in terms of environmental change and thus conducive to dominance by a few fauna. As with the macroinvertebrate infauna, depth is also the most apparent factor controlling epifaunal distributions. The shelf is divided into two major regions based on benthic epifaunal communities; 1) a shallow (10 to 45 m) zone with variable bottom water (10 temperature to 29°C) and salinity (30 to 37 % ) and sandiest sediments; and 2) a deeper region (> 45 m) with 0 more stable temperature (15 to 25°C) and salinity (35 to 37 %o) and high­ est clay content. Subdivisions of these groups are intermediate to these depths and degrees of variability in benthic habitats. Many of the species characteristic of the shallow shelf are motile decapod crustaceans found in inlets, bays and coastal waters in summer and early fall. Large numbers XXIII The demersal fish populations also align with depth on the shelf into three distinct station groups with seasonal migration patterns influencing the species associations. The shallow shelf zone exhibits low species diversity throughout the year with especially high numbers of individuals in winter and spring. The nearshore faunal association dis­ sipates during late summer or autumn when shallow shelf water temperatures are highest. Mid-depth associations are the most diverse and more stable throughout the year. There is considerable species "shuffling” during the communities year in all faunal zones suggesting that species-dominated do not persist. Analysis of physical variables associated with demersal fish populations indicate that sediment mean grain size, salinity, percent silt, sediment skewness, and sediment grain size deviation account for the environmental differences between the depth-related stations. The fish abundance data are substantially less effective in defining station groups than the physical variables. The minimal presence of hydrocarbons in Texas shelf waters and sedi­ ments indicates that the area is relatively pristine with those hydrocar­ bons observed attributed primarily to natural sources. Natural sources include both primary production and bacterial production, in highly active layers near the air-water interface, riverine and estuarine input, water and sediment seepage. Low-molecular-weight hydrocarbons vary considerably both with season and area of the shelf; but higher surface-water methane values are apparent in the more northern, nearshore stations and are probably related to the direct influence of riverine and estuarine factors A unique higher occurrence of deeper waters of Transect IV observed in is attributed to natural across the mud-water this study gas seepage XXIV concentra­ water nepheloid layer, especially in summer, Micro-tarball tions in neuston samples are higher on the two northern transects and may be related to ship traffic in Aransas Pass Inlet and other points in the northern Gulf and also to extensive petroleum activities in waters north of the area. in The lack of evidence for the presence of aromatic hydrocarbons in sediments suggests minimal petroleum pollution. Petroleum pollution the form of micro-tarballs in the water column apparently does not con­ tribute a sufficient quantity of petroleum hydrocarbons to the sediments. of Concentrations of light hydrocarbons in the top few meters shelf and slope sediments are highest nearshore decreasing offshore and are generally of microbial origin controlled by biological oxidation and diffusion into the overlying waters. One area of anomalously high ethane and propane at stations on Transect IV corresponds to the seepage observed in the water column samples and suggests an input of thermocatalytic gas from the subsurface. Studies of the effects of low level and chronic inputs of petroleum in marine biota are complicated by lack of information on background levels of hydrocarbons in unpolluted environments, problems in differen­ tiating petroleum compounds from biogenic hydrocarbons, and the effects of degradation of hydrocarbons, sediment absorption, interstitial water hydrocarbons, and hydrocarbon assimilation in food uptake. Approximately 50% of the zooplankton hydrocarbon samples in 1977 showed the possible presence of petroleum-like matter. This was slightly more than observed in 1976 (30%) and considerably higher than 1975 (7%). These values are higher than similar values obtained for particulate hydrocarbons in the water column, suggesting that the majority of hydrocarbons in the XXV zooplankton values could be a reflection of bioaccumulation and tendencies to of zooplankton concentrate pelagic particulate matter during their feeding activities. Zooplankton will ingest micro-tarballs and other petroleum forms from the water column and them through pass their systems without digesting them. The increase of zooplankton hydrocarbons through the three years may be a reflection of the increased crude oils importa­ tion during this time. The heavy hydrocarbon analysis of macroinvertebrate epifauna and demersal fishes indicates little, if any, petroleum contamination of the area. No significant spatial trends and few seasonal trends suggest of relative stability in the hydrocarbon pools the organisms studied. The studies did delineate an informa­ excellent data base of background tion on indicator organisms for use in future monitoring. The south Texas shelf appears to be free of significant trace any metal contamination in respect to those metals monitored. Trace metal pollution has been found in coastal, industrialized waterways of the area, but there is no evidence of large scale offshore transport of these con­ taminants to the outer continental shelf and thus little contamination of shelf sediments. The only meaningful spatial relationship is an increase in cadmium levels offshore, which is influenced in some way by Aluminum the amount of suspended particulate matter in the water column. decrease with increasing distance offshore and iron levels in zooplankton and also correspond well with observed seasonal fluctuations in suspended matter concentrations in surface waters. The levels of several trace metals in benthic biota are at or below detection levels, and even for metals present in detectable amounts there are no significant geographical trends. Seasonal patterns of aluminum levels in demersal fish are similar XXVI to those of the zooplankton and are a reflection of the more variable nearshore environment characterized by seasonal fluctuations in suspended aluminosilicate matter. particulate XXVII XVIII CHAPTER ONE INTRODUCTION The chemical, physical, and biological interactions both internal and external to the world’s oceans are among the most complex within the natural sciences. If the aspects and processes of these various inter­ actions were understood, their scope and magnitude could be predicted for a given time and place. There are, however, many unknowns that must still be quantified. The Texas coastal area is biologically and chemically a two part marine system, the coastal estuaries and the broad continental shelf. These two components are separated by a chain of barrier islands and connected by inlets or The is rich in finfish and crusta­ passes. area ceans, many of which are commercially and recreationally important. Many of the finfish and decapod crustaceans of this area exhibit a marine- estuarine dependent life cycle, spawning offshore, migrating shore- ward as and utilizing the estuaries as larvae and postlarvae, nursery grounds (Gunter, 1945; Galtsoff, 1954; Copeland, 1965). The broad con­ tinental shelf valuable shrimp fishery which, as supports a a living resource, contributes significantly to the local economy. Although an excellent overview of the of the northwestern Gulf of Mexico zoogeography is provided by Hedgpeth (1953), there are still many unknowns concerning the functioning of this complex marine system. In 1974, the Bureau of Land Management (BLM) as the administrative agency responsible for leasing submerged federal lands, was authorized to initiate a National Outer Continental Shelf (OCS) Environmental Studies Program. As part of this national program, the BLM developed the Marine Environmental Study Plan for the South Texas Outer Continental Shelf (STOCS) to add to our understanding of this ecosystem. This plan was developed to meet the following four specific study objectives: 1) provide information for predicting the effects of OCS oil and gas development activities upon the components of the ecosystem; 2) provide a description of the physical, chemical, geological, and and biological components, their interactions, against which subsequent changes or impacts could be compared; 3) identify critical parameters that should be incorporated into a monitoring program; and. 4) identify and conduct experimental and problem-oriented studies as to meet required the basic objectives. BLM contracted the University of Texas at Austin to act for and on behalf of a consortium of research conducted by Rice University, program Texas A&M University, and the University of Texas, to implement the Environmental Study Plan. This plan called for an intensive multidisci­ to characterize the plinary three-year study (1975-1977) temporal and m water spatial variation of the shelf marine ecosystem beyond 10 depth. In addition to the biological, physical, and chemical components of this program which will be reported here, two other major field programs are conducted concurrently. The U. S. Geological Survey conducted a pro gram designed to investigate suspended sediment flux, normal and storm STOCS area. The National Oceanic and Atmospheric Administration/National Marine Fisheries Service conducted studies to the historical investigate distribution and abundance of ichthyoplankton in the area, to elucidate and and to the snapper grouper fisheries resources, determine the magnitude and economic significance of the recreational and associated "commercial/ recreational" fisheries in the area. In addition to the above studies restricted to the STOCS study area, Texas A&M University conducted a major field survey of the biological and chemical characteristics of selected topographic features in the northwestern Gulf. An is defined as "any area of nature that includes living ecosystem organisms and non-living substances interacting to produce an exchange of material between the parts" (Odum, 1959) The central theme of the STOCS . study was to provide an understanding of the living and non-living resources of the shelf. In order to the objectives outlined above a broad approach program was designed which included: a) water mass characterization; b) pelagic primary and secondary productivity as described by floral and faunal abundances, standing crop, and nutrient levels; c) sediment texture characterization; d) benthic productivity as described by infaunal and epifaunal densities; water e) natural petroleum hydrocarbon levels in biota, and sediment; and. f) natural trace metal levels in biota and particulate matter. of synthesis and integration of the three previous years of sample collection and variable of measurement. The goals this synthesis and integration phase were two-fold: 1. Develop a physical, chemical and biological description of the STOCS ecosystem characterizing with confidence (95%) the temporal of and spatial properties those parameters that best represented the ecosystem between 1975 and 1977. 2, Develop mathematical descriptions for a few unique relationships defined by the data that will serve as "fingerprints'1 for future comparison by managerial decision makers and contribute information to the general conceptual model. It was assumed that understanding the naturally inherent variability of this ecosystem would contribute immensely to evaluating potential impact to the environment from perturbations resulting from oil and gas explore tion and production. Using statistical techniques it was believed that we could integrate the data base to the extent that an initial understanding of a typical marine ecosystem similar to the one depicted in Figure 1 could be docu­ mented, As shall be illustrated in the following chapters, in some cases we were relatively successful in developing an understanding concerning of this overall conceptual model while in other because of parts cases, or the lack of sufficient information either within the data base support­ ing we were not able to add detail to this model. literature, The reporting of the data synthesis and integration efforts for the STOCS Environmental Studies Program takes three forms. This volume i WIND CUKRENib RIVER INFLOW DAL1HII TEMPERA-TURE ESTUARINE FLOW* SEDIMENT-AT10N RESUSPEN-SION* \ — gUNLIGHT^)/ -< (/ / L. / 11 1 11»i ’1 j11« t 2 W1 1 !i« •si*si I_lS[J— I1 1 11•11i •1 * 1 _j 1 '1 \> ~) & Ltyilnl BENTHIC ' ATTACHE!! ALGAE* BENTHIC INFAUNA / -FISH EP1FAUNA LI Lll shelf. — // / / /organic\~W]TRIENTS/ /'yX continental * / / ~4 n7 ' i 1; — INPUTS * FUNGI ~T"1.U&1KUUO MAN Texas I ~ yA \ v/Ij Jfi* 11 N. r 1 I1 r V •~7INORGANia^_o,— south .MJTRIENTS/ \ / x the — of — ZOO-model investigation \r— PHYTO PLANKTON / PLANKTON PELAGIC FISH* PELAGIC -. /->\ r 1 STOCS !i.Lli1HI-111IBIl|l 1i•1 1 / >-conceptual >¦ in sunlight) / studied i CURRENTS RIVER INFLOW* SALINITY TEMPERA-TURE ESTUARINE FLOW* SEDIMENT-RESUSPEN-Ecosystem not WIND ATION* SION* *Elements 1. Figure with (Volume I) is devoted to the program description and history along a presentation integrating all study element results into a characteriza­ tion of the STOCS ecosystem. Within the STOCS ecosystem there are many interrelated physical, chemical, and biological processes. In this volume of some these important factors are described and a conceptual model illustrating the manner in which they interact is developed. Also included in this volume as Appendices A and B is a listing with statistics of all important study variables as identified either by the scientists in the study or by distinguishing spatial-temporal trends. The purpose of these appendices is to provide decision makers and environmentalists assigned to the task of future monitoring with a quick reference concerning certain variables along with their general statistical patterns. ecosystem The second volume in this series (Volume II) is devoted to the data management of the program and includes a description of data file mainte­ nance and archiving as well as the analysis strategies employed in the STOCS synthesis and integration effort. Volume 111 contains the individ­ ual scientific investigator’s reports for the respective study elements detailed during data synthesis and integration. The reader is referred the to these reports for more detail concerning any specific aspects of ecosystem description contained in Volume I. Acknowledgment is given to all the scientists involved in this multidisciplinary program and the contributions they provided in develop­ ing Volume I of this report. For further reference concerning their 111 of see specific contributions, besides Volume the present report, Parker (1976), Berryhill (1977), Groover (1977a), Griffin (1979), and Flint and Griffin (1979). The general area of study corresponds to that portion of the Gulf of Mexico off the Texas coast designated by the Department of the Interior for future oil and gas leasing (Figure 2). The area covers approximately 2 19,250 km and is bounded by 96°W longitude on the east, the Matagorda Bay complex on the north, the Texas coastline on the west, and the Mexico- United States international border on the south. The Texas continental shelf has an average width of 88.5 km and a relatively gentle seaward gradient that averages 2.3 m/km. No ecosystem is a completely self-contained unit, and the STOCS sys­ tem is no exception. It is influenced by adjoining regions such as the open Gulf of Mexico, the Mississippi River to the northeast, the Rio Grande to the south, and the land masses to the west. These adjacent regions have a marked influence on the climate and are the sources of many inputs into the system. Although we can look at the region as a somewhat discrete unit, we must continually keep in mind the influence of these contiguous territories. During the first year of study (1975) 12 sites corresponding to Stations 1-3 on four transects (Figure 3) were sampled. Thirteen (13) additional transect sites were sampled during the second and third year - of study which included Stations 4-6 of Transects I 111 and Stations 1 4-7 on Transect IV (Figure 3) These additional stations were added to . increase shelf of three special areas: 1) the shallow shelf coverage environment (about 15 m depth) and its associated sandy sediments; 2) a zone in the middle of the study area that appeared anomalous in sediment x For hydrographic studies a seventh station was included on Transect II . *V \ — I v \\ SEA\'Ks \ \ CARIBBEAN \ ] * jft r 1l\\mlVy &. \pU| • * ' -*1 f < Mexico. / of STATES » ptCHt YUCATAN ban* Gulf c#kWl of KT UNITED LOUISIANA / the yX W \J* map o - v*ip* \yf EO§ ScAMPECHE MEXICO HOUSTON I \ The / s» L JURE •0.92 calculated >. « ZD«2 I p-/ sampled. s­ 1 > CJlS .¦ (.biD;, CO 1 \o- H -. ¦\£ m m station ,. • ¦ i nr \ 1 \H deviation each . ¦ ~o 1\ m I\ I \a of 1 zo I * standard depth shown. -¦ CJ» Jm - -4. H //* > water . $ salinity are I ¦ a -2 curves O against // Hand / * /¦ o> // oH polynomial w temperature duration >¦ // / . »/ /¦¦ two / study or ¦ the a V / l riot the of ¦/ y b. CJt* ¦ ¦/ • figure ¦ . i i 1 f ro 0__ - 0) — (STD) VARIATION TEMPERATURE BOTTOM —= n: r— sites may suggest the occurrence of occasional upwelling of deep Gulf waters. This is further verified by the plot of temperature cross-section along a transect during the summer of 1977 (Figure 6). Warmest waters are found in surface layers at some distance from the coast. The onshore directed temperature gradient together with the layer of cool near-bottom water extending nearly to the coast indicate the existence of upwelling and a pattern of offshore Ekman transport of surface water with a near- bottom return flow. The summer horizontally isothermal conditions are ideal for this phenomena to occur and are the only opportunity for cross shelf currents perpendicular to the coast to occur with any regularity because of the predominant wind directions from the south-southeast. The graphical summaries of the hydrographic data presented here are useful for quantifying the spatial, as well as the temporal variability asso­ in the hydrographic climate in Texas shelf waters. The time scales ciated with the dominant local variations in temperature and salinity differ significantly between the inner and outer-shelf sites. There was a lack of stratification over the inner shelf at all depths as well as of of the through the surface layers the entire shelf during most summer months. At greater depths, sufficiently removed from surface conditioning by the dominant time scales become too short to air-sea exchange processes, be properly resolved with the available data. If the temperature varia­ tions recorded at near-bottom levels at the outer station are associated with a vertical movement of the top of the permanent thermocline, the associated time scales would be on the order of hour to several days. an This would depend on whether these reflect internal waves or a meteorolo­ gically forced encroachment of water onto the shelf from the open Gulf. t 22 16 18 20-24 20 ;i 7 r-26 J— ,* * * — ~~— 3 1977, 6 August m ** 4 , 1 mm, 1 ' 1 •, 0i_ IX, 5 1 Transect km 30 along *• 2 II \ (°C) cross-section 4,1977 4 ** V Temperature TRANSECT August Temperature * ** 6, 1 o Water Figure --- 0 50 100 O Cn 200 STATIONS 1 DEPTH making a well-defined impression in the hydrographic data of the south Texas shelf. The plume of Mississippi River water, moving westward and southwestward along the northern rim of the Gulf of Mexico during the winter and spring months, is especially pronounced near the coast, but may at times cover the entire shelf. In addition, local rivers and estu­ aries potentially influence parts of the shelf, especially coastal waters, during parts of the year. Examination of trends in a biomass chloro­ phytoplankton indicator, phyll a., provided additional evidence over the study period concerning different water mass influences on the Texas shelf as well as the refine- of Of ment of ideas concerning general physical dynamics the ecosystem. the various processes contributing to the variability of plant biomass the shelf, freshwater discharge appeared to be most influential of across those variables examined during the study. Figure 7 illustrates the rela­ tionship between salinity and particulate matter in the water column. This suggested that as salinity decreases from riverine input the parti- Secchi culate matter increases (decreased depth) along with possible associated nutrients and increased primary productivity. The collection of samples along the transect (II) off the Aransas Pass Inlet to approxi­ mately 90 km offshore for surface water provided an ideal picture of the related to fresh- relationship between lower saline waters, potentially water inflow, and chlorophyll sl concentrations (Figure 8) The highest . monthly concentrations of chlorophyll a were usually associated with lower salinities, usually less than 30 %o* This was especially apparent in the offshore waters in late winter and early spring. In contrast, the variations in temperature (Figure 8) did not appear to play an influential role in chlorophyll trends. Figure 7. Relationship between salinity and secchi depth for all stations. Solid line is arbitrary curve. Numbers refer to months of year. data on based (°C) temperature and s (%o) salinity (yg/£), c± chlorophyll of Contours 8. Figure from extending transect, a along km 1.85 each at 1977 in month every collected points 11. Transect 3, Station to jetties Aransas Port the 32 correlational research Through utilizing salinity patterns, chloro­ phyll a, concentrations and river flow values, it was demonstrated that the STOCS area may be influenced by different freshwater sources depending upon distance from shore on the shelf. Figure 9 summarizes the relation­ ships among chlorophyll a., salinity and freshwater inflow from five point sources hypothesized as influencing the STOCS area. The upper part of the of figure is a plot correlation coefficients vs. distance offshore (km). and The correlation coefficients interrelate the 12 chlorophyll a. salinity values available for successive 1.85 km distances offshore. The zones (marked by vertical lines) within this plot are based on the results of similar correlation coefficient vs. distance offshore plots interrelating point source discharge with either salinity or chlorophyll a,. The zones of maximum negative correlation with salinity (bars) or of maximum posi­ tive correlation with chlorophyll a, (dots) are shown for each point source in the lower part of Figure 9. An inshore zone between 0-14 km offshore is characterized by a high average correlation (-0.76) between chlorophyll a. and salinity and by the highest correlations between Texas point source discharge and salinity. Chlorophyll a, is not well correlated with any point source discharge within this zone. - The middle zone extends from 14 59 km offshore. The chlor­ average decreases Neither ophyll salinity correlation (-0.41) in this region. a_ ­ is well the Texas source discharges nor the Mississippi River discharge correlated with salinity throughout this zone. Texas river discharge, is related to at the inshore side of the zone and Missis however, salinity sippi River discharge is highly related to salinity at the offshore side of this zone. correlations between point source discharge and The major Figure 9. A. Plot of distance offshore (km) vs. the correlation coeffi­cients of monthly chlorophyll and salinity (12 points) for a_ successive km distances offshore. B. The zones of maximum correlation between monthly point source discharge and either monthly salinity (dashes) monthly or chlorophyll a. (dots) for five significant freshwater sources in the northwest Gulf of Mexico. For example, monthly Missi­ssippi River discharge in 1977 exhibits an average correla­tion of -0.85 with monthly salinity readings for every 1,85km between 41-90 km offshore. a north of the sampling transect yield an interesting pattern; the farther away the point source, the farther offshore occurs the band of highest correlation. The Rio Grande exhibits its highest correlation with chloro­ - phyll a. between 39 50 km offshore. The Texas point sources to the north of the cross-shelf transect all abruptly end their high correlation with chlorophyll aat 41 km offshore. This feature divides the middle zone into two subzones; between 14 -41 km offshore, chlorophyll is best - related to Texas freshwater sources; between 41 59 km offshore, chloro­ a phyll is best related to Mississippi River discharge. The offshore zone extends from 59 km to the end of the transect (90 - turns km). The average chlorophyll salinity correlation (+ 0.21) positive in this region suggesting fresh water does not contribute to increased chlorophyll a.. In fact, chlorophyll a shows a tendency to decrease with decreasing salinity. Mississippi River discharge is highly correlated with salinity in this zone. The preceding description provides sufficient information to develop the following model to aid in explaining the potential water mass dynamics on the Texas shelf. 1) Inshore Zone: The dominant force is freshwater from Texas river- is inversely correlated with river discharge ine inputs. Salinity but chlorophyll shows no pattern. Although chlorophyll is highly correlated with salinity, phytoplankton patchiness due to other factors {e.g. sediment resuspension or grazing) in this shallow, well-mixed area apparently confounds a consistent relationship between chlorophyll and river discharge. River influence both salinity Because of mix- and chlorophyll a. freshwater discharge from the different shows sources ing, strong­ est relationships with salinity at the zone boundaries. The cor­ relations inshore of 41 km suggest a strong Texas freshwater pres­ ence while correlations beyond River is indicate the Mississippi the more significant freshwater source. 3) Offshore Zone: Mississippi River discharge dominates the shelf beyond approximately 59 km offshore. The salinity point source discharge correlation is highly negative. The point source dis­ charge correlation with chlorophyll, however, is weak and also shows a negative response. This is intuitively proper since the transit time from source to the STOCS area is probably sufficient to deplete nutrients. From the above described patterns it is possible to more easily understand the gradients that exist on the Texas shelf and why they exist in moving from coastal shallow waters with local influences to deeper more ocean-like waters farther out on the shelf which have very distant influ­ ential processes driving their dynamics. The conceptual model developed of above suggests that many of the dynamics the Texas shelf, such as those associated with pelagic biota, can be explained by considering topography, local river inputs, Mississippi River discharge, and climatic variables such as wind direction and velocity. Between approximately October and March, the currents along the shelf at Aransas Pass Inlet are toward the south-southwest with a pre­ dominant longshore component. Between June and September currents over the Texas shelf are weaker. The over very short time scales and there are often periods of water movement across the shelf, perpendicular to the coast as described above. Drift bottle observations from a separate study (Watson and Behrens, 1970) indicated that most of the currents directly off the barrier islands of the Texas coast were generated by local winds as measured at Corpus Christi, Texas. Nearshore currents were observed flowing in opposite directions during winter and summer, correlated to the prevailing winds. During periods of transitional weather, especially in the spring, south- drift often counter to ward surface was local southerly winds. Apparently the Texas coastal waters are affected by significant currents generated by winds representative of winter conditions in another, probably more northern part of the Gulf, while summer winds have begun to blow in the south Texas region. The seasonal variation in shelf circulation has a direct and obvious effect on the spatial distribution and temporal variability of hydrographic influential factors forcing parameters and suggests possible the ecosystem dynamics. The strong and quasi-steady water flow to the south-southwest during the winter months, and especially into late spring, is responsible the north- for the advective transport of Mississippi River water along western rim of the Gulf of Mexico at a time when discharge is at its maximum. During the summer months aperiodic near-bottom encroachment of water from depths over the outer shelf may play an important role in the ecosystem dynamics during times of relatively low riverine input. The of cross-shelf motion in transporting nutrients, heat, suspen­ importance ded solids and/or live plankton becomes quite apparent. Nutrients observed Nutrient concentrations of the Gulf waters during the study were representative of open Gulf surface waters in most of the water above 60 m in depth, but as illustrated in Figure 7, continental run-off influ­ enced nearshore surface concentrations, especially in the spring. Nitrate, concentrations as the limiting nutrient to primary production,decreased to essentially below detection limits (< 0.1 yM/&) after the spring and early and silicate summer phytoplankton blooms each year (Figure 10). Phosphate were substantially affected by the blooms each year but were never com- These nutrients pletely depleted during summer periods. were generally replenished in the water column during the fall, reaching their maxima in the early to mid-winter period. Contrasts between shallow and deep sites on the shelf for surface water concentrations of these nutrients generally illustrated similar trends with the more distant station from the coast­ line showing proportionately lower concentrations (Figure 7). The excep­ tion to these patterns was observed for phosphate where the inshore sta­ tion appeared to show a completely different trend than the deeper off­ shore station. The intrusion of nutrient rich 200 to 300 m western Gulf waters was often seen below 70 m as indicated by the phosphate concentra­ tion cross shelf contours from Transect II (Figure 11). Oxygen concentrations in the upper 60 m of water varied seasonally being generally highest in the winter and lowest in the summer (Figure 7). The shallower and deeper sites again illustrated similar trends for sur­ face water concentrations. Ratios of measured oxygen equilibrium to oxygen concentrations indicated that oxygen variations in the upper 60 m were generally controlled by physical processes (seasonal hydrographic variability) rather than pelagic productivity fluctuations, Masses of oxygen dissolved and (yH/£), nitrate (yM/£), phosphate (yM/£), silicate of Plot 10. Figure 1977. and 1976 for II Transect 2, and 1 Stations at waters surface the for (ml/£) spring the during II Transect along contours cross-sectional (yM/&) Phosphate 11. Figure (1976), sampling seasonal they were formed nearshore in the water and displaced by warming in the spring and summer. The intrusion of oxygen-poor 200 to 300 m central Gulf water was often evident below approximately 70 m water depth. Sea­ sonal variation of oxygen concentrations through the water column could be seen and were related to the vertical extent of mixing in deeper off­ shore waters. In general, bottom water concentrations observed oxygen - during this study (2,58 5.86 ml/&) appeared to be sufficient to support organisms on the Gulf seafloor. Hydrocarbons The STOCS ecosystem is relatively pristine with respect to hydrocar­ bons, with those observed during this study attributed primarily to natu­ ral sources. Numerous investigators have established that the open ocean Much of is an important source of methane to the atmosphere. the meth­ ane that fluxes at the air-water interface can be attributed to in situ production associated with highly active water layers, in terms of pri­ mary production and possibly bacterial production, within the water column Other natural sources of methane plus other low-molecular-weight hydro­ carbons (LMWH) include riverine and estuarine input as well as sediment seepage. Methane in the northwestern Gulf water column exhibited considerable, seasonal and spatial variability during the study period as indicated by the ranges in Table 4. Higher surface methane values were associated with the more northern nearshore stations of the study area,probably related to more direct influences from riverine and estuarine factors. A relatively unique occurrence of higher methane concentrations was routinely observed in the deeper waters of Station 3, Transect IV during this study. These 2 O 03 pS -Max.] 4000] 578] -21] -10] -4.6] -1.6] -2.6] -2.6] -1.5] -1.3] < - • 0 - - 06 P B * (Min. [41 [44 [0.1 (1.9 [0.1 [0.1 [0.3 [0.4 (0.2 [0.2 H X o\ P 1977 u p P 2 Ed C Mean 239 112 4.5 4.2 0.7 0.5 1.0 1.2 0.5 0.4 vO B r»* 32 3 o Ed 2 P M Obs. 328 54 304 54 273 53 172 54 170 53 gg 1 Q 3 O co P 2 O _2 M B H > O B CJ Ed CO PQ O t*4 methane ethene ethane propene propane O 06 w Parameter Methane surface Ethene surface Ethane surface Propene surface Propane surface mud-water interface at this southern point in the study area. Although the highest near-bottom methane concentrations in the south­ ern part of the study area were assumed to be related to natural seepage, other areas of the shelf did exhibit methane maxima. These were typically associated with a bottom nepheloid layer that is often observed, especially during the summer, on the Texas shelf (Figure 12). Although simultaneous measurements of transmissometry and LMWH were only obtained at a few sta­ tions, it appears that nepheloid layers are common especially at Stations 1 and 2 (and bank stations). Most near-bottom methane maxima in these increases nepheloid layers were accompanied by small in ethane levels. It is uncertain whether high LMWH levels in nepheloid layers resulted from resuspension of bottom sediments containing higher LMWH levels and/or from in situ production associated with the layer. Higher nutrient and productivity levels associated with these layers may result in high in situ rates. production Table 4 lists concentrations of ethene, ethane, propene and propane during 1976 and 1977. The unsaturates dominate over their saturated analogs in most areas of STOCS, with exceptions generally occurring at water depths greater than 100 meters. Propene concentrations were almost four times lower than ethene concentrations. There was always good agree- in 1976 and 1977 between average olefin concentrations. ment The level of total dissolved and particulate organic matter generally to found in the Gulf of Mexico aquatic ecosystem is in the range of 0.1 1.0 pg/&. Accurate knowledge as of the initiation of this study had not been obtained on ranges of hydrocarbon values in these same waters. Recent data collected from other systems (McAullife, 1976; Koons, 1977) Figure 12. Depth profile of methane, ATP, chlorophyll a_, and trans­missometry (nl/&) in the STOCS area near Station 2, Transect II for September 15, 1976. are located in the surface microlayer of the water column and that these concentrations decrease rapidly within the first 10 m of water depth. Concentrations of dissolved and particulate high-molecular-weight hydrocarbons were similar in magnitude (Table 5). Particulate hydrocar­ bon concentrations generally decreased with distance offshore. Higher concentrations of particulate hydrocarbons at inshore stations appeared to result from terrigeneous input through direct addition of particulates and increased primary production at shallower sites. Dissolved hydrocar­ bon concentrations showed less variation. Concentrations averaged higher for winter and spring than for fall samples. Proportion of dissolved and particulate hydrocarbons varied similarly. The most abundant n-alkanes were in the C27-C33 with a slight preference for odd carbon numbers range TABLE 5 AVERAGE TOTAL HYDROCARBONS IN SEAWATER BY STATION (DEPTH) FOR ALL TRANSECTS Total Hydrocarbons , Dissolved + Particulate <(ygM) Station 1 Station 2 Station 3 1975 0.43 0.31 0.20 1976 0.34 0.25 0.21 1977 0.46 0.31 0.33 AVG. 0.41 0.29 0.25 Particulate Total Hydrocarbons (yg/£) Station 1 Station 2 Station 3 1975* 0.11 0.10 0.05 1976 0.13 0.06 0.05 1977 0.35 0.11 0.12 AVG. 0.20 0.09 0.07 Dissolved Total Hydrocarbons (]ig/£) Station 1 Station 2 Station 3 1975* 0.16 0.11 0.15 1976 0.20 0.19 0.16 1977 0.11 0.20 0.21 AVG. 0.16 0.17 0.17 V * Fall season only PELAGIC BIOTA OF THE SOUTH TEXAS SHELF with contributions by: D. L. Kamykowski P. L. Parker R. S. Scalan J. K. Winters University of Texas, Marine Soienoe Institute, Fort Aransas, Texas E. T. Park P. Turk J. H. Wormuth L. H. Pequegnat J. McEachran B. J. Presley P. N. Boothe Texas A&M UniversityCollege Station, Texas 3 Phytoplankton The hydrographic environment of any marine shelf ecosystem can be very complex because there are so many factors capable of influencing the dynamics of the system. The STOCS area is no exception with influences such as western land masses and associated riverine inputs, the deeper offshore Gulf waters, and possibly most important, the Mississippi River to the north. Previous work both on the Texas shelf and other shelf eco­ systems has suggested that the hydrographic features and many of the biotic components, especially pelagic aspects, are strongly correlated. Hydrographic variables such as temperature, salinity, and currents pre­ sented in the preceding chapter, illustrate the annual progression that occurs over the south Texas shelf and help to suggest possible factors of that influence the functioning the ecosystem. General patterns in phytoplankton biomass on the Texas shelf during the 1975-1977 study period are best illustrated by examining changes at the three stations on Transect II which were sampled monthly over the 1976-1977. 13 period Figures through 15 summarize the temporal and depth patterns in the nanno (a), net (b), and total (c) categories of chlorophyll a. at the three stations of Transect 11. Station l/II (Figure 13) is tem­ porally characterized by a continuous background concentration of nanno­ chlorophyll a,; concentration peaks occur in the April and Fall (Hurricane Anita) cruises of 1977. Net chlorophyll a_ is much more variable exhibiting a seasonal peak occurrence between November and May. The seasonality in total chlorophyll a. concentration is dominated by the net fraction. Sur­ prisingly, the water column is routinely inverted in chlorophyll a. concen­ trations, i.e. the maximum concentration occurs in the bottom waters. Station 2/II (Figure 14) exhibits less variability in the nanno­ fraction than Station l/11. The concentration of nanno-chlorophyll a., however, generally exceeds that of the net fraction. Two exceptions are at the surface, April 1976 and bottom, July 1977. The total chlorophyll a_ concentration reflects the nanno trend except during the net fraction peaks. The vertical profile of chlorophyll again routinely exhibits an a_ increase with depth. Station 3/II (Figure 15) exhibits a further decrease in nanno­ chlorophyll variability. An exception occurs at the half-photic zone, winter 1977. The net fraction is extremely low except for the winter of 1977. The total chlorophyll category reflects the even distribution of the other two categories throughout the sampling period except for the combined nanno and net peaks. This unusual concentration of chlorophyll a. 1977. at all depths is related to an upwelling during February This event Figure 13. Station 1 chlorophyll _a (yg/£) at the surface (1), half the depth of the photic zone (2) and bottom (5) in the -a) nanno, b) net, and c) total categories plotted against sampling period. Figure 14. Station 2 chlorophyll (yg/£) at the surface (1) half a_ ? the depth of the photic zone (2), and bottom (5), in the a) nanno, b) net, and c) total categories plotted against sampling period. Figure 15. Station 3 chlorophyll a. (yg/il) at the surface (1), half the depth of the photic zone (2), and bottom (5), in the a) nanno, b) net, and c) total categories plotted against sampling period. occur may every year but may be easily missed in most sampling programs because of its probable short duration. Analysis of variance (ANOVA) results of the general chlorophyll a, trends illustrated above showed that the cross-shelf was statis­ gradient < tically significant (P 0.05) for all components of chlorophyll at all depths. The bottom samples, however, exhibited a slightly different pat­ tern from the surface or half the depth of the photic zone collections within these general trends. The latter showed that Station 1 was signi­ ficantly different from Stations 2 and 3. For bottom water concentrations, on the other hand, the nanno and total chlorophyll categories were similar at Stations 1 and 2 while both these collection sites differed from Sta­ tion 3. There was also a north-south chlorophyll gradient observed on the shelf although it was not as strong as the cross-shelf gradient. The < northern part of the STOCS was significantly (P 0.05) higher in chloro­ phyll a. both at the surface and half the depth of zone than the photic the southern part of the shelf. Measures of chlorophyll in the bottom waters, however, did not show a north-south gradient. These patterns may reflect Mississippi River influences on the shelf which significantly decrease in their impact on the southern collection sites. That the bot- do illustrates lack of mixing on tom waters not show the same patterns the outer shelf. Figure 16 summarizes the temporal patterns in the nanno (a), net (b), and total (c) categories of carbon 14 uptake at the three stations of Transect II during 1977. Stations 2 and 3 dominate the winter nanno Station 1 is dominant over the rest of activity; the majority of the year. The inshore peaks in nanno activity occur in spring and fall. Station 1 dominates the net activity during the spring and November; Station 3 domi­ Figure 16. Stations 1, 2 and 3 surface carbon 14 uptake (mg C/m 3/hr)­in the a) nanno, b) net, and c) total categories plotted against sampling period. The net peak precedes the nanno peak in the spring bloom and follows it during the fall bloom. The total category presents the composite of the size fractions and provides a picture of classic zone temperate phyto­ plankton activity. concentrations observed The chlorophyll during this study, especially in the shallower shelf waters plus the phytoplankton activity represented by Figure 16 suggested that the Texas shelf may be extremely productive in terms of primary producer biomass. Utilizing a technique developed by Ryther and Yentsch (1957), which estimates primary production based upon chlorophyll ji measures and light transmittance through the water column, a two-year production curve was developed for Station 1 of Transect II (Figure 17). Primary production for Texas inner shelf waters (Figure 17) is somewhat bimodal annually with peaks in the spring and fall. Annual estimates of production, based upon the chlorophyll a_ measures converted to carbon equivalents, indicated that these waters produced a mean of 2 103 approximately g C/m /yr. In contrast, estimates of primary production for coastal waters of other continental shelves that support substantial fisheries, as the STOCS does, such as the North Sea (Steele, 1974), indi­ 2 cate an of 70 to 90 C/m/yr. It that the annual production g appears Texas shelf can be considered an extremely productive ecosystem in terms of plant biomass. In terms of species composition, the phytoplankton community structure of the STOCS to area is complex but relatively consistent with respect In different water masses that occur on the shelf over the annual cycle. the general, the progression of community structure through seasons occurs at different rates at different locations on the shelf. The results of waters coastal Texas for fixation) (carbon production primary of cycle year two The 17. Figure to according measures chlorophyll from estimated fixation Carbon 1977. and 1976 between . (1957) Yentsch and Ryther of technique structure of the phytoplankton are related to light intensity, day length, temperature, salinity, stratification, wind and nutrient sources. The patterns observed over the study period demonstrate the complexity of phytoplankton response to conditions on the Texas shelf. Species groupings derived from the cluster analysis of phytoplankton are less informative than the station groupings. This results from both reasons. counts technical and biological Technically, the phytoplankton are generally limited to the size fraction above 20 y. Since this fraction is dominant only between December and April, the species groupings repre­ sent successions only within this time period. The cruises were not suf­ ficiently frequent to adequately distinguish community changes within this limited period. Information on summer community structure was also limited by the fact that the greatest concentration of phytoplankton occurred near bottom where species composition samples were not available. The biologi­ cal reasons are related to the low sampling frequency compared to the rate of change of phytoplankton species composition. The species lists are usually very different from one cruise to the next. Considering these the problems. Figure 18 depicts seasonal patterns of the phytoplankton classes and Figure 19 depicts the seasonal pattern of selected phytoplank­ ton species or genera from the net phytoplankton observed at the surface along Transect II during 1976 and 1977. The graphs are ordered by decreas­ ing numerical abundance. are Diatoms, dinoflagellates, and silicoflagellates generally most abundant between the November and Spring cruises through the winter months (Figure 18). The remaining time interval is represented by a minor dino­ flagellate peak, coccolithophorids and blue-green algae. Figure 18. Comparison of seasonal abundances of Che different classes of phytoplankton observed along Transect II during 1976 and 1977. Each point represents the sum of the surface abundances at Stations l/11, 2/II and 3/II within a sample period. Number of Individuals (cells/1) are plotted against Julian Day. The graphs are ordered by decreasing abundance. Figure 19. Comparison of seasonal abundances of different species or genera of phyto­plankton observed along Transect II during 1976 Each point and 1977. represents the sum of the surface abundances at Station l/11, 2/II and 3/II within a sample period. Number of individuals (cells/i) are plotted against Julian Day. The graphs are ordered by decreasing abundance. two years are different in the order of species appearance. In 1976, a relatively clear succession occurs: Winter -Gonyaulax polygramma and Prorooentrum mioans; March Thalassionema nitzsohioides ; April Skele­ - tonema oostatum Nitzsohia spp., Chaetooeros spp.; Spring Triohodesmium 3 spp.; August and Thalassionema nitzsohioides. In - Gonyaulax polygramma - 1977, more co-occurrence is evident: Pre-March Chaetooevos spp., Rhizosolenia Thalassionema nitzsohioides Cevatium and Trioho­ spp., , spp. - desmium November Rhizosolenia spp.; spp. a The patterns present confused picture of the phytoplankton community. This probably results from the complex hydrography in the STOCS area. the to Better information on specific dynamics according shelf-influencing factors may be obtained by eliminating geographic stations and relating species assemblages in similar water masses as was done with the chloro­ phyll a. observations presented above. Nepheloid Layer As stated previously, the highest concentrations of chlorophyll sy were often observed in the bottom waters of the shelf (Figure 13) especially at the shallow stations on the shelf. The bottom water is also charac­ terized by a pervasive nepheloid layer (Berryhill, 1977) at least during part of the annual cycle. Data from several cruises in 1978,t0 examine nepheloid layer dynamics, not only demonstrated prevalent nepheloid levels (Figure 20), but also illustrated the presence of peak chlorophyll layers in the bottom waters, as well as peaks in nitrogen represented by ammonia. These peaks of primary producer biomass as well as greater than transmissions these 1% light at depths suggested the possibility of photo­ synthesis taking place. Carbon 14 experiments confirmed this (Kamykowski Figure 20. Depth profiles of percent light, transmissometry, chloro phyll a. two and ammonia nitrogen concentrations for cruises off the Texas coast (33 m water depth) during 1978 near Station 4, Transect 11. and Batterton, 1979). In addition to the primary producer biomass in bottom waters there appeared to be a considerable amount of nutrient regeneration as illustrated by the ammonia concentrations (Figure 20) The basic conclusions drawn from the study of the nepheloid layer during four diel sampling cruises in 1978 were: the 24-hr 1) The nepheloid layer was present throughout sampling period and fluctuated in thickness and density within this period; 2) Phytoplankton are concentrated in the nepheloid layer during the summer months in the STOCS area. Active carbon fixation can occur since 10% surface radiation may often reach the sediment interface in the zone within 50 km of shore; 3) Since nutrients are probably supplied to the layer at least partly from benthic diffusion, the phytoplankton dynamics of the layer may be affected by perturbations of the benthos caused by oil-related activities; 4) The overall impact of this effect depends on organism sensi­ tivity, the area perturbed, exchange intensity and the trophic significance. Neuston The neuston is defined as plants and animals that live on or just beneath the surface film of marine waters. Sargassum mats are usually associated with this of the Texas as well surface component shelf waters as some freshwater plants such as water hyacinth which enters the system through riverine inflow, especially farther south near the U.S.-Mexico border. Very diverse communities of fauna,are normally associated^with with the more free-living fauna that inhabit this surface zone. It is felt that many potential pollutants that enter the marine system do so through the surface waters {e.g. petroleum hydrocarbons) and any biologi­ cal impact from these pollutants may first manifest itself in changes to the neuston. Although the neuston defies a strict biological definition in terms of species, there are certain taxonomic groups which are commonly found in the upper 15 to 20 cm of the water column during significant portions of each day. There is considerable variability not only in the abundance of neuston, either as total numbers of organisms or dry weight, as well as taxonomic composition. This is due, in part, to diel vertical migration, but also to various types of environmental heterogeneity. Day-night sampling helps to minimize the former variation, but the latter source of variability is not generally monitored. The number of organisms and densities of these organisms collected from all stations for each season varied widely both within taxa and was temporally (Table 6). Neuston biomass also highly variable during the study interval. Most taxa showed distinct seasonal cycles with peaks occurring during the spring and summer sampling periods. In contrast, a few late fall-winter species were found. These general trends showed good year-to-year reproducibility. Onshore-offshore variation was observed some in the distribution of taxa,particularly the larval decapod crusta­ ceans , The neuston decapod fauna was studied in great detail during 1976 and 1977. A total of 104 decapod taxa were identified consisting of 88 larval taxa and 16 non-larval taxa. Decapod larvae accounted for 53% of the mean concentration of total decapods and 6% of the total neuston. 63 (u) 560 a­ 1052 1105 11004 480 478 108 114 757 955 177 X --­ UPPER females 1537 2155 5808 29311 59366 41955 1265 1294 3319 3885 1491 6517 5068 8144 2405 1748 11549 Centropages vellficatus . 3 u ---------------------­ 2513 10563 72905 11929 m 3 10 ZERO. 58027 11 24 8 930 123 445 159 677 829 NUMBER/ CROSS females I 594 -22433 X -­ 1331 1661 3317 4165 5215 4529 4507 3071 Calanopla amerlcana N u -----------------------­ - IN NOT 2068 48 I -------­ GIVEN DID HEADED 1273 5859 619 ARE THEY 152 551 327 738 426 178 379 355 701 131 X--­ 3962 1494 6159 2737 3127 9214 2775 1838 2824 zoea 11593 12903 12021 COLUMN Brachyuran - u ---------------------­ 255 6650 4931 NUMBERS WHEN THE 18182 ONLY £­ 2968 1538 DAY. UNDER GIVEN X----­ 6 OF 447 11897 165 13620 23 1584 696 430 12698 105 2768 8129 1659 11105 325 14808 6169 1269 7229 4001 815 4452 ARE GIVEN Brachyuran megalopa TABLE u ------------­ TIME 22427 10800 AND LIMITS ARE 625 1367 5695 6502 1475 faxonl 125 230 757 35 57 X --­ 3988 2874 5844 9684 2609 9285 3638 6426 3130 3502 1777 1874 1385 CRUISE 60424 13132 101362 29771 15637 22024 BY CONFIDENCE OBSERVATIONS I Lucifer u --------------------­ 4381 5634 5528 115152 19761 OF TAXA 95% 2447 3877 .(£) NUMBER 19480 SELECTED i -­ 84 99 7589 41 X 413 -343 805 636 817 4554 2653 2411 5451 6184 1898 LOWER Hyperldae 17176 31349 14443 36624 85268 29355 28495 OF u ------­ AND 31905 151055 53563 N -3 33 3 7 132213 1 213213 1212 --611 1112 ABUNDANCES MEAN Day Twilight Night Day Twilight Night Day Twilight Night Day Twilight Night Day Twilight Night Day Twilight Night Day Twilight Night Day Twilight Night Day Twilight Night CRUISE WINTER MARCH APRIL SPRING JULY AUGUST FALL NOVEMBER DECEMBER 102 X 1371 1706 757 5299 741 159 534 866 59 429 477 -700 i 472 ---­ 9118 6951 2171 5307 4114 7182 3507 1497 6247 14767 Fish eggs 965 ' - --_---­--_--_ 6348 u ----­ 13663 t ---------------­ 44 302 382 -604 7 265 79 7262 427 577 430 233 722 341 543 205 133 961 357 125 424 113 Fish larvae X 3068 1601 8 2555 3584 3859 1405 u -------­ 809 852 1061 2597 136 1656 609 210 5674 5073 4009 1­ 6573 11917 309 720 477 362 X 1804 8776 3130 7731 3821 1336 2306 4539 2718 4575 2111 8733 5443 1777 5412 5440 21746 12468 22998 11350 Chaetognaths u ---------­ 2998 11878 10388 7431 18362 34078 13456 t -------------------­ 884 1506 8 4016 35 24 90 177 110 145 989 516 222 636 474 297 vlllosa males 2367 61450 2428 3714 2184 2036 1943 2968 Pontellopal CONT.'D X -­ ---------------_ u---­ 3849 2861 6 I -------------------_­ 202 414 44 41 347 984 113 232 599 159 590 237 189 517 X TABLE 1207 3169 5360 8089 7006 1393 Immatures 13743 100612 184046 26664 Labldocera --------_------_--_­ u­ 995 2372 -_ ---­ t ----_--------_ _ 3193 19 966 ­ 4793 8264 9233 2068 X _--_---------- Anomolocera ornata Immatures 11782 13792 20098 9567 u 20370 854 151 _ -676 ----------_ ~ t ---­ 6357 14792 17797 518 671 780 159 507 118 365 1592 1904 1638 6542 218 3836 4219 6027 3208 1579 1311 1514 41 3360 X 17273 97112 47760 Temora styllfera - ------_ _­ u _­ 3131 6726 6817 1408 179432 77722 ---— -------------_ t -­ -269 2349 Minor 616 8520 358 21792 40 16428 1071 2176 990 1265 133 240 9 526 2666 489 2554 _---_­ - X Nannocalanua -------_-----_-_--_ _ 4082 u 14691 in winter and greater at nearshore stations than at offshore stations. The decrease in larval diversity with distance from shore could be expected since decapod larval input into the surface waters is greatest over inshore areas where benthic decapod adult populations are more diverse and there is the direct influence of estuarine input to the system. Nearly all of the dominant decapod larvae reached greatest concentrations during the spring. A large number of fish taxa occur in the neuston off south Texas for at least part of their life span; most have distinct seasonal, diel and horizontal distribution cycles. The neuston fauna consisted of a cold water component, present either from fall through winter, or from winter through early spring; a warm water component, present either from late or a spring through summer entirely during the summer; and übiquitous component present in high abundance most of the year. Within each of the seasonal components, taxa were generally distributed either inshore or offshore and were present in the neuston zone either nocturnally or diur­ nally. of for each of Diversity fish taxa, when computed the sampling years, == was relatively high (H ? 2.72 for 1976; H T 2.58 for 1977). In 1976, the most abundant taxa (those which individually represented 2.5% or more of the total) were: Antennarius sp. (22.6%), Harengula caguana (11.9%), Mugil cephalus (8.6%), Mullidae (8.1%), Opisthonema oglinum (4.4%), Cynos- Gerreidae cion sp. (4.2%), (3.8%), Engraulus evrystole (3.0%), Mioropogon undulatus (2.9%), and Citharickthys spilopterus (2.5%). With the excep­ tion of Antennarius sp. which was captured at only three stations, these taxa were widely distributed over the survey area during at least one of the sampling seasons (winter, spring-summer, fall). In 1977 the most abundant taxa, representing 2.5% of more of the total,were: Mullidae (18.1%)., Etrumeus teres (12.9%)., Harengula jaguana (8.5%), Gerreidae (4.7%), Traohurus lathami (4.6%), Raohycentron oanadum (4.0%), Mugil ourema (3.3%), Prionotus spp.. (3.2%), Mugil oeghalus (2.6%), and Mentioirrhus sp. (2.6%). All of these taxa, with the exception of Raohycentron oanadum , were widely distributed over the survey area during at least one of the sampling seasons (winter, spring-summer, fall). The Gerreidae, Prionotus and Mentioirrhus were spp. spp. each represented by in the area. several species survey of variance of tar concentrations collected in neuston tows Analysis showed significant differences according to season and transect but not station or time. To illustrate this, tar concentrations were highest dur­ ing March and September-November. In part this was due to single high values which shifted the means upward. Figure 21 shows variations on tar ball concentrations with transect in the STOCS area. Highest averages were observed Transect I and II with dramatic decreases on Transects on 111 and IV. It should be noted that Transect II was sampled more consis­ tently (monthly) during the study period which may account for the higher mean concentrations. The trends suggest, however, that presently the surface concentrations of hydrocarbons may be related to ship traffic in the Aransas Pass Inlet and other points in the northern Gulf and extensive petroleum activities in the waters off Louisiana, north of the STOCS study area. The only significant correlation for neuston biomass observed during this study was with the amount of tar obtained in the same samples. Two One surface theories may possibly explain this phenomenon. concerns circulation which creates convection cells, i,e. Langmuir cells (Pollard, 1977). If tar is considered to be a passively floating object, then it of number the represent numbers The transect. by concentration tar in points. variation coincident The 21. Figure rows. The positive correlation then may suggest that neuston, in general, are also concentrated in windrows to some extent. An alternative explanation may be related to the nutrition of neus­ ton. It has often been observed in Gulf waters that small fish and larger crustaceans (i.e. crabs) are frequently associated with small floating pancakes of mousse and tar balls. These included observa­ reports have tions of the fauna feeding off the tar and mousse. There is a very good likelihood that well-weathered petroleum products floating in the Gulf surface waters develop growths of epiphytes and other colonial forms normally associated with hard surfaces. These growths on the floating tar could possibly be providing a food source to many surface-oriented species including neuston. Neuston cluster grouping results showed patterns consistent with water temperature trends. Thus it could be concluded that the dynamics of the neuston may be controlled by temperature, which is the influential factor related to spawning of many of the temporary populations found in the neuston. In general, the faunal composition of the neuston differed from that of the water column below the neuston zone. Finucane (1976, 1977) reported on the ichthyoplankton captured in the water column from the stations sampled in this study and found a number of differences same between the species composition of the two. Fishes of the neuston zone can be classified as facultative neustonic taxa or euneustonic taxa. Those of the former category are found in the neuston during the larval stage while those of the latter category spend their entire life history in the neuston. Facultative forms dominate the neuston and a majority their juvenile in the estuaries and of these spend and adult stages inshore waters of the northwestern Gulf of Mexico. Diel variability played a large role in influencing the dynamics of the STOCS neuston. In addition, distance from shore played a role for the many taxa, particularly the decapods, probably due in large part to benthic distribution patterns of the adult species and estuarine influences Zooplankton Zooplankton biomass, total density, and female copepod density decreased with distance offshore. When only the means were considered (Figures 22 and 23), biomass weights not only decreased seaward but varied most consistently between seasons at the shallow stations. Mean total zoo plankton densities varied similarly in a seaward decrease, but seasonal fluctuations by depth were poorly patterned. Mean densities of female copepods changed with the total zooplankton, decreasing with depth. Spe­ cies diversities followed the same patterns of change with depth and sea­ son that were observed in the number of species. The mean equitabilities, however, showed almost pattern of change related to depth or no season. The relatively low mean values obtained for equitability at each depth, indicated that a few species accounted for most of the zooplankton density across the shelf. The dominant female copepod species observed during this study are illustrated in Figure 24 along with their frequency of occurrence at sta­ tions along Transect 11. Copepod species formed five species groups which were generally related with water depth (station location) on the transect. The first group was generally considered übiquitous in nature. Group 2 was confined to the shallower waters on the shelf. Group 3 to mid-depths, and Groups 4 and 5 to the deeper waters. In addition to the general trends Figure 22. The mean (circles) and 95% confidence interval (bars) for of four representative zooplankton variables (average transects for each station and season). \ Figure 23. The mean (circles) and 95% representative zooplankton sects for each station and confidence intervals (bars) for variables (average of four tran­season). Figure 24, The frequency of occurrence of female copepod species used in cluster analysis for each bottom depth (= station 1-3 in order of increasing depths). Maximum number of occur­ rences -36. depth stations on the Texas shelf usually differed during the semi-annual periods from' December-June and July-November. The results of representative zooplankton variables such as biomass, total zooplankton density and female copepod density revealed consider­ able variation in zooplankton distribution along bottom-depth contours from transect to transect during each of the nine seasonal cruises. The variability suggested the occurrence of pulsing inputs to the systems which encouraged zooplankton production but which were so limited that the entire length of the study area was not uniformly affected. For example, the calanoid species Acartia tonsa Paracalanus indicus Para­ 3 3 calanus quasimodoand Clausooalanus furcatus were often found in dense , patches on one or two transects in the spring. Cladocerans, Penilia spp., appeared in a highly regionalized dense patch at Station 1, Transect II in the spring of 1977 and in August 1976. Ostracods, primarily Euoon­ choecia ohierchiae , were found in dense patches at various stations throughout the study. It is possible that the patchy distribution of the zooplankton in the study area was related to pulses of low salinity input from bay sys­ tems. Evidence for estuarine influence in the STOCS area may be found in the composition of copepod species. Aoartia tonsa is a calanoid cope- pod which is almost always reported among the most abundant copepod species inhabiting bays and estuaries in the Gulf of Mexico and along the Atlantic coast from Florida to Cape Hatteras (Breuer, 1962; Cuzon du Rest, 1963; Bowman, 1971). In the STOCS area Acartia tonsa appeared in large numbers in 1975 at the nearshore and mid-depth stations on Transects I and II in the spring. In all three years Acartia tonsa was most abundant in the spring when salinities were low and the largest abundances in other aestiva Oithona nana and Paraoalanus erassirostr-is) also most were 3 abundant. Multiple regression analysis identified possible relationships between zooplankton densities and physical, nutrient and phytoplankton variables. A number of expected, or at least plausible, relationships were indicated; entities however, occasional relationships between trophically separated (i.e phosphates and copepods) suggested that some of the relationships . may be deceptive. At the shallow stations, changes in ichthyoplankton more frequently related to the variation in zooplankton variables than any of the other independent (physical or phytoplankton) variables. This were to may indicate that ichthyoplankton populations possibly responding changes in zooplankton density. It is generally accepted that some spe­ cies of planktonic fish take advantage of the zooplankton as a food source (e.g. Peters and Kjelson, 1975). Salinity, although related to several zooplankton community charac­ teristics at the shallow stations, was more often highly correlated with these at the mid-depth stations. The implied relationships between zoo- plankton variables and salinity at the mid-depth stations may indirectly reflect a response of the zooplankton to changes in primary production which have been shown to be commonly associated with salinity changes in neritic waters. The number of associations between zooplankton and phytoplankton variables increased seaward. At the deep stations, phytoplankton density generally accounted for the largest percentages of explained variation in zooplankton variables. The implied direct relationship of zooplankton to of phytoplankton at the deep stations reflects a close dependence zooplankton on phytoplankton which is generally reported for oceanic, subtropical or tropical areas of marine waters (Menzel and Ryther, 1961; Sander and Moore, 1978). The combined results from the three depth con­ tours suggested that offshore zooplankton populations may be controlled by food availability while nearshore zooplankton populations may be con­ trolled by predation. Results from studies of microzooplankton on the Texas shelf indi­ cated that protozoa reached a maximum in abundance in early spring (March-April). A second protozoan abundance peak was noted in September 1977 but this peak was thought to be atypical and a result of Hurricane Anita which passed through the area at that time. Oligotrichs were the dominant protozoan group on the STOCS, both spatially and temporally. The other protozoan groups tended to be more restricted both in space and time. Species diversity was high during most of the year and varied erratically. Protozoan biomass ranged from 1 to 348% of the macrozoo­ of plankton biomass, indicating that protozoa are a significant component the zooplankton community. Zooplankton Body Burdens Hydrocarbons 50% of the taken in Approximately zooplankton hydrocarbon samples showed 1977 the possible presence of petroleum-like organic matter. This was slightly more than was observed for samples in 1976 (30%) and con­ siderably higher than observed in 1975 (7%). This apparent increase may be a reflection of the increased import activities for crude oils during this time interval. The criteria for presence of petroleum-like organic matter are smooth distribution of n-alkanes in the region of molecular size greater than samples analyzed by gas chromatography/mass spectrometry (GC/MS) tech­ niques, the presence of aromatic compounds is usually indicative of petroleum-like material. Seven zooplankton samples were investigated by GC/MS analyses in 1977. One sample, 3/IV, spring, contained polynuclear aromatic hydro­ carbons (PAH) in quantities such that they were readily identified even though the quantities were too inadequate for the components to be observable in the gas chromatographic analysis. Four samples (l/11, spring; 2/111, spring; 3/11, spring; 1/IV, spring), showed possible trace quantities of PAH by GC/MS analysis, though quantities were inade­ quate to permit certain identification. Two samples (2/IV, winter; l/111, fall) showed no indication of the of PAH. All seven of these presence met the n-alkanes distribution criterion as samples possibly having petroleum-like organic matter present. OEP Although relatively high values were observed for particulate hydrocarbons in the water column, these values were considerably lower than values found for zooplankton in this study. Zooplankton average OEP values for nine seasonal sampling periods ranged from 2.0 to 15.4 with an of 5.8. The comparatively low values of OEP average for parti­ - culate hydrocarbons (0.9 1.6) suggested that the majority of these The hydrocarbons were not synthesized by zooplankton or higher plants. values observed could have reflected the bioaccumula­ higher zooplankton tendencies of tion and concentrating zooplankton for pelagic particulate matter their feeding activities. It is well documented in general during (Conover, 1971) that zooplankton will ingest micro-tarballs and other petroleum forms from the water column and pass them through their systems without digesting them. This is also a mechanism for input of petroleum hydrocarbons to the benthos via zooplankton fecal pellets. The usual range of total hydrocarbon concentration in zooplankton or was 50 to 500 pg/g. Total hydrocarbons did not show either temporal None of spatial variations that were significant. the isoprenoid param­ eters were shown to vary in a statistically significant manner. Seasonal averages of concentrations in the zooplankton hydrocarbon region of C25--C32 (which represent the sum of highest carbon ranges of high molecular weight hydrocarbons) as well as the seasonal average OEP values are plotted in Figure 25A. Since both parameters were estimates of the quantity of petroleum hydrocarbons, they were considered as a single data set from which a curve was constructed. The large standard deviation associated with both parameters results from the ’’patchiness" of zooplankton and petroleum hydrocarbons likely present as micro-tarballs In view of the difficulty in obtaining representative samples composed of two components each having its own unequal distribution, the fit of points to the curve is rather good. The data (Figure 25A) suggested a signifi­ cant increase in the contribution of petroleum hydrocarbons to zooplankton samples during the three-year study period. Exploration and drilling activities in the study area probably were not a major source of petroleum residues found in the zooplankton samples, A much more likely source would be the oil tankers which delivered increased quantities of crude oil to Texas ports during the study period. The quantity of crude oil imported to the Port of Corpus Christi and Harbor Island from 1975 through 1977 has been plotted in Figure 258. The curve generated by the data of Figure 25A has been included in Figure 258 for comparison, and the two show a good correlation suggesting potential causes of hydrocarbon increases. 25. of samples 1975-1977. Figure A,_ Average Sum Hi CCzs-Csz) and average OEP zooplankton B, Crude oil Imported to the Port of Corpus Christ! and Harbor Island 1975-1977, Curve from A has been included in B for comparison. Table 7 summarizes the three years of zooplankton trace element data by station and transect sampled. The only truly meaningful spatial effect observed in zooplankton was an increase in Cd concentrations offshore. The reason for this trend is not clear. The trend does not suggest any significant anthropogenic input of Cd to the nearshore environment. Secchi 2 depth, however, was strongly correlated with Cd levels (r= .30). This parameter is a measure of turbidity and suggested that zooplankton Cd levels were influenced in some way by the amount of suspended particulate matter in the water column. Table 8 summarizes the seasonal concentrations of trace average metals in zooplankton observed during this three-year study. Aluminum, Fe and Ni exhibited significant seasonal trends. Elevated levels of A and Fe in zooplankton samples are generally interpreted as incorporation Consid­ of clay particles by the zooplankters (Martin and Knauer, 1973) , for the seasonal erable evidence suggested that this process is responsible trends observed here. The concentrations of A 1 and Fe in suspended matter from the Gulf of Mexico were approximately 9% and 5%, respectively (Trefry was 0.56. and Presley, 1976a). The Fe/Al ratio in such particulates Aluminum and Fe levels in zooplankton samples from this study were strongly correlated (r2 = .81) and the average Fe/Al ratio was 0.52. In addition, the trend in zooplankton A 1 and Fe concentrations (Table 8) corresponded well with the observed seasonal fluctuations in suspended matter concen­ trations in STOCS concentrations surface waters. Suspended particulate are generally highest in the fall and lowest in the spring (Berryhill, 1978) Also A 1 and Fe levels in zooplankton decreased with increasing . distance from shore. These geographical trends for zooplankton were Ca 35000 30000 35000 30000 65000 30000 60000 50000 30000 25000 40000 4000 NS NS (14000-40000) 4500-60000) (22000-65000) (16000-45000) 8000-140000) (16000-50000) (18000-100000) (25000-80000) (25000-35000) 9500-35000) (10000-70000) (35000-50000) (( ( 6500) 3000) 1 (1900-19000) 100-10000) 12-25000) 75-14000) 95-12000) 850-30000) (1300-30000) 300-17000) 550-20000) 80-25000) A NS 7000 2500 140-2200 5500 4000 2500 7000 6000 4500 4500 9000 1500 200-.008 ( (( ( (( (((( STUDY .05) mean) 500) 210) 160) 250) 500) 190) 270) 500) 500) Zn 120 125 130 130 180 110 130 140 220 170 350 180 NS NS (p STOCS 75-1300) (9.0-2000) 80-1000) > 95-25-22-40-30-35-75­ around (9.0-(6.0­ ( ((( (((( ( significant THE observed V 21 161614 251510 132413 NSNS 9.5 7.0 not FROM (4.0-45) (1.2-20) (1.4-25) (0.4-70) (2.2-65) (2.0-25) (4.0-60) (3.0-70) (3.5-35) (4.5-50) (2.3-85) (5.0-25)Interval means NS75) 13) 70) 70) 65) 40) Pb 22 13 7.0 11 11 12 1510 23 12 NSNS 8.5 7.0 ZOOPLANKTON confidence (1.8-160) (1.4-(0.60-45) (0,80-40) (0.80-30) (0.80-40) (0.55-140) (0.60-shown. (1.3-(1.3-(1.0-(0.6­(95X level IN -11) -15) -16) -30) -18) -18) -17) -16) -40) -8.0) N1 10 NSNS 8.5 6.0 8.0 5.0 7.0 6,5 5.5 7.0 7,0 6.0 5.5 7 weight (0.60-20) (0.95-30) at (2.0 (3.0 (2,2 (1.9 (2.0 (3.0 (2.0 (2.0 (2.0 (3.0 TABLE ELEMENTS dry significant ppa 5000) 3900) 8500) 8000) 6600) 1600) 550 NS .005 in Fe 4500 1900 1200 3000 2100 1600 3000 3000 2500 3000 5000 was TRACE (400-13000) (100-(130-35-13000) (240-17000) (550-(350-11000) (200-12000) 24-15000) 20-40-70­ ((( (( Indicated OF 90) 60) 20) 30) 35) 55) Concentration 70) 75) 2500) 300) Cu 142124 20 21 161413 135017 NSNS (5.0-23) (6.0-90) (9.5-(2.5--(7.0-(5.5-(8.0-(6.0-(6.0-(8.0-(7.5-effect (5 main CONCENTRATIONS 190 NS NS Cr 6.0 4.5 2.5 4.0 3.5 2.5 4.5 4.5 3.5 3.0 5.5 4.0 (0.10-22) (0.35-14) (0.40-6.0) (0.70-14) (0.50-9.0) (0.10-7.5) (0.60-13) (0,30-10) (0.75-8.0) (0.45-8.5) (0.11-16) (0.10-11) the which fur AVERAGE -6.0) -7.0) -5.5) -7.0) -5.5) -6.0) -6.0) metals Cd 1.4 3.0 5.0 2.4 3.5 5.0 2.0 3.5 4.5 3.0 3.0 4.0 NS .001 (0,65-3.0) (0,95-5.5) (0.65-4.0) (0.80-4.5) (0.60-4.5) (1.6 (3.0 (1.8 (3.5 (1.5 (1.8 (2.5 1 results: m• 1 182012 162012 182012 161812 O 1!2 Transect Station ANOVA Itiiu%i23 123 123 123 1 MU•• 9M H 11 IV I 111 Ca .005 30000 45000 50000 (9500-50000) (16000-90000) (16000-95000) indicates (*) 5000) 1300 .001* A1 4500 (250-13000) 11000 (100-25000) Asterisk (75­ STUDY mean) .05). 500) 200) > STOCS Zn NS 160 130 (p around 220 (9.0-1000) (25-(40­THE FROM observed significant effect. V NS 13 (4.0-40) 13 (1.3-65) 25 (4.0-45) not hat t Interval means -45) Pb15 NS NS ZOOPLANKTON (1.5 7.5 (0.60-45) 14 (0.65-80) included confidence IN shown. which 5) made 8 N1 ELEMENTS (95X 5.5 (2.0-9. 6.0 (1.9-18) 9.5 (1.6-25) .001* level weight teatsTABLE the dry TRACE ppm at ANOVA .001* 950 (23-3500) 5500 (30-15000) In OF Fe 2-wav 2300 (120-6000) Sept.-Oct. significant was Fall in Cu NS Concentration 15 (4.5-45) 16 (6.0-38) 70 (5.5-210) jth effect ilcant CONCENTRATIONS -be Hay-June; slenll main NS ­ 4.0 (0.60-8.5) 3.5 (0.10-10) 5.5 (0.15-14) Cr season was Spring SEASONAL effect which -6.0) for main Cd 3.5 .022 3.0 (0.85-5.0) (1.1 3.0 (0.65-6.0) Jan.-Feb.; AVERAGE metals season “ of Winter 5670 68 Number Samples Results: 1 o Seasons: ANOVA Season Winter Spring Fall Season 12 effect. As a result they could not be considered completely clear cut. Still, they were consistent and followed suspended matter concentrations which also decreased offshore (Berryhill, 1978). CHAPTER FOUR MARINE BENTHIC ENVIRONMENT OF THE SOUTH TEXAS SHELF with contributions by: E. W. Behrens University of Texas Marine Science Institute Galveston Texas 3 , P. L. Parker R. S. Scalan J. K. Winters University of Texas Marine Science Institute Fort Aransas Texas 33 J. M. Brooks B. B. Bernard Texas ASM University College Station Texas 3 3 General Features The primary topographic features of the STOCS are the deltaic bulge seaward of the Rio Grande, the comparable outline of an ancestral delta near the shelf edge seaward of Matagorda Bay, the Colorado-Brazos, and the broad ramp-like indentation on the outer shelf between the two deltaic bulges. Second order topographic features are the north-to-northeastward trending low ridges, terraces and low scarps over the ancestral Rio Grande delta, the series of small enclosures associated with a band of irregular topography (e.gHospital Rock, Southern Bank) along the ramp between . water depths of 64 to 91 m and the terrace-like area along the outer shelf beginning at the 91 ® isobath. In general, the remainder of the sea floor is characterized by sand sized sediments on the inner shelf which decrease in abundance seaward. The surficial and near-surface bottom sediments are typically relatively soft and not suitable for bearing heavy structures at shallow depths cated along the periphery of the ancestral Rio Grande delta. Where firm relict sand and soft mud are locally adjacent, seafloor stability is highly variable over short distances. Rapid rates of local sediment deposition or scour have not been observed for this area. According to results of the 1975 study on STOCS summarized by Berry- hill (1977), sand is being transported seaward from the high energy zone of the innermost shelf. The presence of thin, discrete sand layers in the subsurface sediments to a distance of at least 18 km offshore suggests that transport of sand occurs over a relatively short time and is influ­ enced by short-lived events. The encroachment of sand particles into the Texas shelf from a southward movement of the north suggests regional sedi­ ment. A feature peculiar to the outer continental shelf of the northwestern Gulf of Mexico is the series of banks or pinnacle-like topographic highs rising abruptly from the generally smooth, sediment-covered bottom (Parker and Curray, 1956) Two of these, Hospital Rock and Southern Bank, were . studied in conjunction with the STOCS survey. In addition, a series of inshore irregularities between 26° and 27°N latitude (near Transects 111 and IV, respectively) include scattered rock, shell and sand banks at 20 to 30 m and 50 to 80 m and a series of inshore elongated troughs and ridges from 10 to 18 m (Mattison, 1948). Some of these features have been determined to be of lacustrine origin (Thayer et al,1974) as well as 9 remains of an earlier more northerly extension of the Rio Grande delta system. STOCS study transects did not incorporate any of these features. Sediment Structure The 25 transect stations sampled during 1975-1977 on the south Texas a wide range of textures from silty clays to muddy sands. Stations varied enough so that each could be treated as having unique characteristics. More efficient or meaningful comparisons with other data could be obtained, however, if generalizations were based on groups or gradients of textural data. The most distinctive group was the outer shelf clays. These graded from finest, best-sorted, and least variable texture for the outermost stations (7/IV, 6/111, 3/111, and 3/II) to slightly less well-sorted, siltier, more variable stations (2/111, 5/111, 5/11, 6/II and 3/1). These deepest stations generally displayed mean grain sizes of 8.5 to 9.6 0 and averaged only 5% sand and 33% silt. Station 5/1 was very simi­ lar to this group but was more variable. Station 6/1 was similar in vari­ ability but slightly coarser and less well-sorted with a mean grain size of 7,7 0 and 18.5% sand. Station 4/111 was most characteristic of the outer margin (shoreface) of the barrier island sand body where variability was low,probably because wave action could constantly maintain a fairly well-sorted texture. Slightly seaward of this zone, sand usually remained predominant but was mixed with considerable amounts (20 to 50%) of shelf mud (Stations 1/1, 4/1, 1/IV, and 4/IV). The stations on Transect I had fine to very fine sand as the coarse fraction while those from Transect IV had much coarser sand and some gravel in the coarse fraction. The rest of the stations on Transect IV (3, 4, 5 and 6) were charac­ teristically very poorly sorted, variable mixtures of fine gravel to fine clay. High sample variability suggested that bottom conditions were least uniform in this environment with abundant patches of both very clayey and coarse, sandy sediment. In addition to being related to physical energy intensity and vari­ material. Thus, where older sediments are being reworked into more recent material on the Rio Grande delta, there is relatively high variability. The highly variable Station 5, Transect I may be similarly related to the ancestral Colorado-Brazos delta sediments at the northern margin of the study area. Maximum variability was characteristic of a zone just seaward of the boundary of shoreface sands (Stations l/II and l/III). Fine sand consti­ tuted between 10% and 40% of the sediment and was apparently distributed very heterogeneously on scales from centimeters to tens of meters. Ade­ quate statistical in this zone and on the Rio Grande delta would sampling require the largest number of replicates, probably more than has been used in the BLM studies. The last of Stations mid-shelf group (2/1, 2/II and 4/II) represented muds of moderate variability. Although the means for these stations were generally in the silt range, silt was almost never predominant, and rela­ tive amounts of sand, silt, and clay were extremely variable with each ranging from 20% to 40%. Consequently, sorting was poor with a mean of 3.5 ±0.30. The degree of in-station variability did not correlate closely with seasonal textural changes. In fact, significant seasonal significant changes tended to occur in regions which had the most uniform sorting. that seasonal changes were due to active rather This suggested processes than to variability of repositioning stations on successive sampling cruises. and Four stations (.1/11, 2/111, 5/TV, 6/IV) showed significant sea­ sonal changes in sediment texture. The change was an increase in coarse a ness during the spring accomplished by both an increase in sand and decrease in clay with little change in silt content. This may have resulted from winnowing of clays and some fine silts during the spring when seasonal winds were at a maximum. The high spatial variability of the Rio Grande delta and the high probability of at least error one navigational having occurred in this region (Station 6/TV) however, made navigational variance a slightly more plausible explanation in this case. Station 6/IV was among the group with a high percentage increase in sorting with the addi­ tion of possible seasonal effects, but no other indicators suggested a be real temporal change at this station, and none was believed to signifi­ cant. The remaining five stations that showed significant seasonal changes were 1/1, 2/1, 3/1, 3/11, and 4/11. The seasonal changes at Station 3/II followed the most widespread, significant seasonal changes observed in 1976. Those were spring coarsenings at the outer shelf, clayey stations accomplished by reduction in the quantity of finest clays C> 10 0), Sta­ tions 6/1, 4/11, 5/II and 6/IX, also followed this trend, but most of these stations lacked the precision LORAC navigation on the spring cruise when coarsening was observed. Furthermore, the spring coarsening was caused by complex variations in sand, silt, and clay contents rather than just loss of fine clays. Many stations (3/1, 3/111, 5/111, 6/111 and 7/IV) in the outer-shelf group showed no pattern or opposite seasonal trends. Consequently the trend apparent in the 1976 data of spring coarsening on the outer shelf by winnowing of the finest clays had little support from the 1977 data. In contrast to the outer-shelf stations, the inner-shelf stations with high sand contents (30 to 80%) showed similar coarsening trends throughout 1977. Although changes at Station 4/111 were relatively small, the small intrastation variance made them significant. Coarsening occurred whereas fall fining at this station. Significant spring coarsening also occurred at Station 1/1. All coarsening at inner-shelf stations accompanied increases in sand content and decreases in mud content, resulting possibly mud from sand deposition, erosion, or both. If sand deposition occurred, it would imply a general offshore movement of sand from the barrier shore- face. This and mud erosion may have resulted from an increase in wave climate. The coarsening effects apparent in the fall seasonal samples may have been related to such an increase resulting from the passage of a hurricane just south of the study area the fall sam­ in August preceding cruises. The effectiveness of this event was some fall pling supported by coarsening at all inner-shelf stations, although Stations 4/1, 1/IV and tests of 4/IV did not pass significance. Station 2/1 varied similarly to the inner-shelf stations during 1977 in that an increase in sandiness caused the spring texture to be signifi­ cantly coarser than the texture for the winter samples. There was no sig­ nificant change, however, between spring and fall at this station. On the other hand, Station 3/1 showed spring fining and fall coarsen- These ing, changes apparently resulted from clay deposition in the spring and silt deposition in the fall. These events represented the deeper water equivalents to coarser particle deposition at the inner-shelf sta­ tions. of the south Texas shelf sediment structure The preceding description can be summarized by reference to several sediment variables listed in Table 9 and illustrated geographically in Figure 26. These variables are categorized according to station groupings similar to those listed above but also represent major biotic zones of the benthos which are described in detail in the next chapter. The textural gradients offshore OTHER TABLE 9 THE MEAN AND STANDARD DEVIATION () FOR SEVERAL SEDIMENT VARIABLES FOR THE STATION GROUPINGS DEFINED BOTH FROM COMMUNITY ORDINATION OF BENTHIC SPECIES LISTS AND DISCRIMINANT ANALYSIS, ANALYSIS OF VARIANCE INDICATED SIGNIFICANT DIFFERENCES (P < 0.01) BETWEEN ALL GROUPS. LEAST SIGNIFICANT DIFFERENCE RESULTS FOR INDIVIDUAL GROUPS NOT SIGNIFICANTLY DIFFERENT FROM EACH (P < 0.05) ARE INDICATED BY OVERLAPPING HORIZONTAL LINES OR SIMILAR SUPERSCRIPTS Variable Group 1 Group 2 Group 3 Group 4 Transition Stations Group 5 Depth 15.0 18.5 33.6 67.7 84.6 125.0 (8.8) (0.0) (10.2) (18.6) (13.3) (10.3) Mean Grain Size 4.10 4.90 7.47 6.68 8.74 9.45 (0.51) (0.42) (0.98) (1.57) (0.70) (0.23) Grain Size Deviation 2.60 3.57 3.46 3.86 3.15 2.90 (0.48) (0.27) (0.27) (0.43) (0.26) (0.15) Grain Size Skewness 2.56 1.28 0.37 0.38 -0.03 -0.27 (0.84) (0.32) (0.31) (0.46) (0.22) (0.10) Percent Sand 79.2 65.4 22.1 40.3 8.3 3.2 (6.1) (6.5) (14.6) (21.5) (6.1) (2.4) Percent Silt 9.8 13.3 35.6* 19.5 34,8* 30.3 (3.0) (3.1) (8.2) (7.5) (5.3) (2.1) Percent Clay 11.0 21.3 42.3 40.2 56.8 66.5 (4. 'll (4.6) (9.8). (14.1) (9.2) (3.0) Sand/Mud Ratio 4.66 2.14 0.36 0.90 0.10 0.04 (1.2) (0.7) (0.3) (0.6) (0.08) (0.04) Silt/Clay Ratio 1.25 0,65* a 0.89 0.49* a 0.65* ‘ 0.46 a 0.02) (0.19) (0.25) (0.04) (0.18) (0,05) Similar superscripts indicate no significant differences between groups according to LSD test. - *a Figure 26. Geographical representation of different shelf zones where sediment characteristics are relatively similar within the zone on the south Texas shelf. Each shaded area a station represents group which has the depth and sediment characteristics listed Table 9. on form texture from sample to sample as indicated by mean grain size and its standard deviation (Table 9) which sometimes showed a seasonal tendency to coarsen by winnowing of finest clays during the early spring at Sta­ tions 3/1, 3/11, 3/111, 6/111, and 7/IV. A slightly more vari­ coarser, able silty clay occurred at Stations 5/1, 6/1, 5/11, 6/11, and 2/111. These were transition stations (Table 9) between deeper clayey sediments and the silty sediments of the mid shelf (Figure 26). There was quite a variable sand-silt-clay, mid-shelf mixture at Stations 2/1, 2/II and 4/II in the northern part of the study area and further landward the most vari­ able inner-shelf, sandy muds occurred at Stations 1/1, l/11, l/111, 5/111, and 5/IV. These comprised Station Group 3on Table 9. A similar group of stations with somewhat more variability at least partly because of a much coarser sand (Table 9) mode with some gravel included Stations 2/IV, 3/IV, and 6/IV on the Rio Grande delta (Station Group 4), Stations 4/1 and 1/IV (Group 2) had moderately variable muddy sands near the bar­ rier shoreface sand-offshore mud boundary, while Stations 4/111 and 4/IV (Group I) were within the shoreface sands where variability became as low as at the outermost stations due to the efficiency of wave action constantly sorting the bottom sediments in shallow water (Table 9). At the inner- shelf stations there was also a suggestion of seasonal coarsening in early spring and a year-long coarsening in 1977 perhaps related to hurricane generated waves between spring and fall sampling. Sediment Chemistr 13 The results of the Delta C and total organic carbon analyses for the shelf sediments are summarized in Table 10. There was clear a very trend of increasing total organic carbon with distance from shore (P=.001). TABLE 10 13 SUMMARY OF SEDIMENT DELTA C AND TOTAL ORGANIC CARBON DATA PERCENT (IN PARENTHESES) Transect I Nearshore Mid Shelf Offshore Line Average Winter -19.92(.72) -20.40(.88) -20.24(1.02) -20.18(.87) Spring -19.58(.47) -20.50(1.06) -20.46(1.04) -20.18(.86) Fall -19.24(.58) -19.68(.94) -19.89(.56) -19.60(.69) Yearly -19.5S(.55) -20.20(.36; -20.20(.38) =13V99C.”S1) Transect II Winter -20.35(.70) -20.35(.38) -20.50(1.12) -20.40(.90) Spring -20.17(.93) -20.38(.39) -20.36(1.13) -20.30(.93) Fall -19.43{.82) -19.65(1.02) -20.24(1,28) -19.77(1.04) Yearly -19.93(.32) -20.12(.93) -20.36(1.13) -20.17(.97) Transect III Winter -19.75(.94) -19.90(1.02) -20.10(.84) -19.92(.94) Spring -19.54(.44) -19.95(,97) -20.32(1.12) -19.94(,84) Fall -13.94(.42) -19.93(1.01) -19.38(1-30) -19.60(.91) Yearly -19.40(.60) -19.94(1.00) -20.10(1.08) -19.82(.90) Transect IV Winter -19.40(.73) -20.10(.77) -20.30(1.10) -19.99(.90) Spring -19.13(.23) -19.75(.79) -19.9K.79) -19.6K.62) Fall -IS.32(.21) -19.99(1.75) -20.26(.36) -19.36(,94) Yearly -19.30(.50) -19.94(.32) -20.16(.52) -19.82(.82) BANK STATIONS SB HR Bank Average Winter -20. 35(1.01) -20.30(.70) -20.32{.36) Spring -20. 26(1.04) -20.38(1.12) -20.32(1.08) Fall -20. 32(1.03) -20.19(1.22) -20.26(1.12) Yearly -20. 31(1.03) -20.29(1.04) -20.30(1.04) Transect I Transect II Transect III Transect IV Nearshore 4,1 1,4 4,1 4,1 Mid Shelf 2,5 2,5 5,2 5,2 Offshore 6,3 6,3 3,6 6,3,7 coefficient = .76). There was also a significant change (P = .001) in 13 13 Delta C with more positive ( C enriched) values nearer shore. Delta C is a measure of carbon enrichment or depletion. A negative value 13 under these circumstances represents an enrichment of C and depletion 12 of C in respect to a standard with a value of 0. Seagrasses are more 13 C enriched than plankton (Calder, 1977; Fry, 1977) and this trend may represent the export of seagrasses from the estuary to the shelf. The bank stations were uniform. very 13 The rather uniform pattern of Delta C and the low values of total at organic carbon suggest that petroleum pollution a fairly gross level 13 could be detected by Delta C shifts. If oil of Delta Cl 3 equal to -30 is added to sediment at a level to shift the total organic carbon level 13 from 0.5 to then Delta C will shift to a value between -20 and -25. 1.0, 13 Such a total organic carbon shift could undetected but such a Delta C go shift would be easily noted. Even if the oil lost its chemical identity as a hydrocarbon, due to partial oxidation and incorporation into cells, 13 the Delta C shift would persist. Statistical analyses provided only weak evidence for temporal and spatial variation of sediment total hydrocarbons. The data suggested sediments contained slightly higher total hydrocarbons in fall, interme­ diate values in winter and lower values in spring. Transect 111 stations to had highest concentrations; Transect II had mid high values; and Tran­ sects I and IV had the lowest values. Statistically significant seasonal effects were noted for the sum of the hydrocarbons between Cii+-CiB (SUM LOW) in 1975 and 1976 data. Sea­ sonal changes in SUM LOW may reflect biological activity and molecular values for SUM LOW could result from increased production of these com­ pounds in the water column or at the sediment-water interface. Microor­ ganisms within the sediment consume the added organic matter including lower molecular weight hydrocarbons and produce their own characteristic hydrocarbon distribution which contains a larger percentage of higher carbon number alkanes. Sediment SUM LOW therefore decreases as primary decreases. production of lower molecular weight hydrocarbons Long-term temporal changes in sediments were also observed for mid range hydrocarbons between Ci9-C2i+(SUM MID) and the higher ranged hydro­ carbons between C2O-C32(SUM HI). The data presented in Figure 27 indi­ cates a significant increase in SUM HI (P = ,001) and concommitant decrease in SUMMID = (P .001) over the three-year study. No significant change in OEP HI (G25--C32) was observed over the study period despite the tremendous increase in SUM HI (C25--C32). OEP MID (Cl- Czh) did, however, show a significant change (P = .001) as a result of the decrease in SUM MID (Cl9-021+). The lack of change in OEP HI and the changes which did occur in SUM MID and OEP MID that the increase suggest in SUM HI during the study period was due to natural processes rather than the direct addition of petroleum hydrocarbons. in The lack of evidence for the presence of aromatic hydrocarbons sediments suggested minimal petroleum pollution of STOCS sediments. Pet­ roleum pollution in the form of micro-tarballs observed in the water col­ umn (zooplankton samples) apparently did not contribute a sufficient sediments quantity of petroleum hydrocarbons to to significantly change sediment OEP HI or permit detection of aromatics. Concentrations of low-molecular-weight hydrocarbons in the top few 3 % Q2 S3w 40 ranges. fO Au 35 o -25 -20 -15 -.0 -5 J F (C25-C32) Hi Sum S "T 1977 and TW i 19-Can) >i (C r Mid nr F \ ) Sum the . S in 1976 1 < n-alkanes TW . ( - y/ sediment F of r s L 1975 Percentage • 27, W ( 90-05-80-75-70-65-60-55-Figure • vO0^ X 23in by the existence of anomalously high methane concentrations in the top sediment layers. Apparently, bacterial production of methane is not restricted to the sulfate-free zone, but also occurs within microenviron­ ments in sediments having near-seawater interstitial sulfate concentrations. Two meter vertical methane profiles in nearshore sediments exhibited maxima ranging from 100 to 500 ]i£/£ (pore water), Figure 28 is a schematic representation of interstitial methane in the upper four meters of sediment based on samples taken in the STOCS area as compared to slope and abyssal sediments examined independently. The diagram illustrates the disappear­ ance of the maxima as well as the trend of decreasing interstitial methane in an offshore direction. These trends were associated with variations in temperature and microbial activity. Interstitial concentrations of ethene, ethane, propene, and propane 60 in nearshore decreased progressively from 160 to n£/£ (pore water) sediments, to fairly uniform levels of 80 to 25 n£/£ downslope, respectively These trends are illustrated in Figure 29, which shows average concentra­ of Transect I stations tions of the four hydrocarbons throughout the cores which were sampled independently for comparison of shelf and slope low­ molecular-weight hydrocarbons. The trends of the Cz and C 3 hydrocarbons with distance from shore were similar to the behavior of methane. These patterns suggest that the concentrations of Cz and C 3 in the top few meters of shelf and slope sed­ iments were Like methane, concentrations of the microbially supported. oxidation Cz and C 3 hydrocarbons are probably controlled by biological and diffusion into the overlying waters. The concentrations illustrated in Figure 29 generally represent Figure 28. Schematic diagram of methane variations in the upper four meters of sediment. Figure 29. Average concentrations of the C 2 and C 3 hydrocarbons at Transect I stations. Note that stations 49-51 were sample' independent of this study and the data are presented for comparison of shelf and slope sediments. shelf. One area of anomalously high ethane and propane was found, how­ ever, suggesting an input of thermocatalytic gas from the subsurface. Figures 30 and 31 show ethane and propane concentrations with sediment depth at the Transect IV stations as compared to Transect 111 stations. Corresponding to the seepage observed in the water column at Transect IV (pg. 44, Chapter 2), sediment low-molecular-weight hydrocarbon showed anomalously high concentrations at Stations 4,6, 3 and 7 along this transect. The stations along Transect 111 were typical of the normal distribution of low-molecular-weight hydrocarbons from biogenic sources in the shelf sediments. Interstitial ethane and propane concentrations varied between 20 and 40 n&/£ in this area. Ethane and propane concen­ trations along Transect 111 (Figure 30 and 31) tended to decrease in an offshore direction with ethane levels generally slightly higher than pro­ pane, in a manner very similar to Transect I (Figure 29). The northwestern Gulf of Mexico, including the STOCS area, appears to be free of any significant sediment trace element contamination. Metal pollution has been observed in sediments from Corpus Christi Bay (Neff et at,, 1978; Holmes et at,, 1974), the Houston Ship Channel-Galveston Bay area (Hann and Slowey, 1972), the Mississippi River delta (Trefry and Presley, 1976a) and a few inland waterways (Slowey et at,, 1973). There is no evidence of large scale offshore transport of these contami­ nants to the outer continental shelf and thus little contamination in shelf sediments This situation is (Trefry and Presley, 1976b). not unex­ pected, especially for the STOCS area, which is not highly industrialized. Anthropogenic trace elements, along with other materials are trans­ ported to the ocean from continents by freshwater discharges (e.g. sewage storm outfalls, runoff and river discharge) and atmospheric processes. Figure 30. Interstitial ethane concetrations (nl/& pore water) at stations along Transects 111 and IV. Figure 31* Interstitial propane concentrations (nl/£ pore water) at stations along Transects 111 and IV, sippi and Atchafalaya rivers account for more than 95% of the fresh water entering the northwest Gulf (Berryhill, 1977). The discharge points of these rivers are located at approximately 700 and 500 km, respectively, from the study area. In addition, all rivers on the south Texas coast (except the Rio Grande) discharge into bays and estuaries which are sep­ arated from the Gulf by barrier islands. Without the major industrial areas on the coast and the lack of any the south Texas direct local riverine impacts to shelf, high trace metal concentrations in the shelf sediments would not be expected. In general, these trends have been verified by previous work in the northwestern Gulf (Berryhill, 1977). Any localized concentration of trace metals in the sediments along the edge of the shelf were attributed to suspected natural gas seepage. Offshore gradients of very low trace metal levels were also shown to be directly related to increases in clay content of these sedi­ ments. BENTHIC BIOTA OF THE SOUTH TEXAS SHELF with contributions by: P. Powell P. Szaniszlo University of Texas, Austin, Texas W. E. Pequegnat C. Venn C. S. Giam P. N. Boothe B. J. Presley J, R. Schwarz S. Alexander Texas ASM University, College Station, Texas R. W. Flint N. N. Rabalais J. S. Holland R. Yoshiyama D. E. Wohlschlag University of Texas Marine Science Institute, Port Aransas, Texas One of the major focuses of this multidisciplinary study on the south Texas shelf was characterization of the subtidal benthic habitat from near- shore to the shelf slope. As stated by the International Council for the Exploration of the Sea (ICES Cooperative Research Report #75, 1978), "a number of field studies are documented that have as their basis the large identification and enumeration of the species occurring in a community, many of which are concerned with the relatively sedentary benthos on the basis that these species will be unable to avoid adverse conditions. Thus, the status of such populations at any point in time is likely to reflect the conditions that prevailed over a relatively long preceding period”. of The benthos represents an important component any aquatic ecosystem water masses motion, the benthos is relatively stationary and as such serves as a barometer reflecting changes that occur in localized areas within the ecosystem. Except for the species with obvious commercial importance, however, the benthos has not received the attention necessary to completely explain the natural variation or to follow the transfer of materials through the communities to which these species belong. It is believed that benthos serves as one of the essential links in the trophic dynamics of many of our more important fisheries such as the Gulf of Mexico shrimp fishery. Microbiology Marine Fungi Fungi are übiquitous in both terrestrial and aquatic environments. It is somewhat surprising, however, that the predominant genera and spe­ cies found in sublittoral marine sediments are the same members saprobic of the Fungi Imperfecti that are commonly found in terrestrial habitats (Steele, 1967). Despite their documented abundance and the fact that they occur in sediments as viable mycelial filaments (Johnson and Sparrow, marine 1961), the free-living higher fungi have been largely ignored by mycologists who have directed their attention to yeasts and less abundant, but uniquely marine, groups of algal parasites and wood rotting fungi (Jones, 1976). The ability of fungi to degrade alkane (Markovetz et at., 1968) and aromatics (Cerniglia et at., 1978) hydrocarbons is well docu­ mented, but the factors controlling the fungal degradation of crude oil in marine sediments are as yet largely unknown. The study of sediment the fungi on the south Texas outer continental shelf is timely because of activities in the rapid increase in petroleum development and production area. in 1977. Population densities ranged from a low of five Colony Forming Units per ml (CFU/ml) in winter samples from Station 3/1 to a high of 1600 CFU/ml in the fall samples from 3/II (Table 11). The average for the year in the study area was 236 CFU/ml sediment. There was a progression toward larger fungal populations beginning with the late-winter low and ending with a significant (P < 0.03) increase in the fall. An exception to this trend was seen at the deep station on Transect I where fungal abundance was much greater in the spring than in the fall. The annual pattern of increasing numbers of fungi through the fall period was paral­ leled by an increase in generic richness, an index of community diversity (Table 11). of When the abundance of fungi capable degrading petroleum products, as measured by assaying the growth of pure isolates on crude oil, was 52% of the total 83 benthic compared to that of non-hydrocarbon degraders, isolates tested were observed as capable of assimilating crude oil (Table 12). It was clear that a greater proportion of fungi from the shallow stations than those from intermediate depth stations were capable of degrading oil (Table 12). Oil degradation potential decreased offshore. Crude oil stimulated the growth of benthic fungi (Figure 32), The addition of South Louisiana Crude Oil (SLCO) to fall benthic sediment samples resulted, after 45 days, in an average 7-fold increase in fungal abundance at the 0.5% (volume/volume) oil level and a 3.6-fold increase at the 0.1% oil level relative to the control. There was, however, an ini­ tial inhibition of the natural mixed fungal populations in the 0.5% treat­ ment. This initial toxicity was also seen in experiments with pure cul­ tures of Candida diddensii in which pre-starved inoculum and low nutrient conditions duplicated as nearly as possible STOCS ecosystem conditions. SEDIMENTS Mean 98 248 359 SURFICIAL 571 Fall 200 200 910 450 160 1600 ± 10.3 STOCS 587 IN SEASON** 11 RICHNESS AND SEASON Spring 33 30 20 83 350 15 89 ± 130 7.0 TABLE FUNGAL ABUNDANCE (CFU/ml)* AND GENERIC BY BOTTOM DEPTH Depth Station/ Transect Winter Shallow X/II 110 1/XV 16 Intermediate 2/II 11 2/IXX 12 Deep 3/1 5 3/IX 21 Season Mean 29 ± 40 Generic Richness Avg. No. Genera/Station 5.8 *Colony Forming Units/ml wet sediment **0ne-way ANOVA with season as independent variable F= 4.8331, df = 2, 13, P= 0.024. TABLE 12 GROWTH OF FUNGAL ISOLATES* IN CRUDE BT STATION AND DEPTH OIL Depth Station/Transect Growth No Growth Shallow Intermediate Deep l/II 1/17 2/II 2/III 3/1 3/IX 11 13 5 3 3 8 6 9. 9 7 3 6 By depth. 1C2 * 4 .916 0.05 < P < 0.1 D.F. -2 *Isolated from benthic sediments on nonselective medium Figure 32. 'Effect of crude oil concentration on fungal growth in natural mixed cultures of STOCS benthic sediments diluted (1:5) with artificial seawater. The numbers are the mean values for all samples from the fall 1977. (•) 0.5% oil (SLCO) ; (O) 0.1% oil (SLCO) ; (.) control to which no oil was added. from0t03%oftheno-ailcontrol. Maximumtoxicityoccurredbetweenthe third and sixth days with recovery and significant stimulation taking place by the 22nd day. The abundance of fungi in the STOCS benthic system appears to be controlled by two factors: 1) the replenishment of inoculum from the water column, a seasonal phenomena; and 2) the availability of organic the carbon, a site specific parameter. In general genera of fungi observed during the study were those whose spores are usually most abun­ dant in the air over the adjacent land masses. The species most frequently encountered in sediment samples during this study Cladosporium alado~ were sporioides (Freson.) deVries, Fenioillium oitrinum Thom, Aspergillus flavus var. oolunmaris Raper and Fennel, Aspergillus sydaui (Bain and Sart.) Thom and Church, Fusarium ventrioosum Appel and Wollenweber and F, monili­ forme var. suhglutanans Wr. and Reink. The terrestrial origin of these genera was also suggested by higher abundances observed in the nearshore stations (Table 11). The large increase in benthic fungi isolated in the fall can be explained by the early fall arrival in the sediments of spores suspended throughout the summer at the thermocline/pycnocline following their depo­ sition in the water column during late winter and spring. As the atmo­ spheric spore load in Texas is reaching its annual maximum (Chapman, 1979), the last continental air masses of spring are moving out over the Gulf of Mexico off Corpus Christi in late April or early May (Orton, 1964). Until fall the area is covered by maritime air masses. These conditions are reflected in the abundance of fungi in STOCS near-surface waters (Szaniszlo, 1979). During March and April of 1977 fungi were uniformly very abundant with monthly averages of 40,000 and 16,000 CFU/£ compared to only 13 CFU/& 110 The number of colony forming units of benthic marine fungi observed in the fall samples was directly correlated with the total organic carbon = concentrations of these sediments (r 0.843). Indirect evidence also miner- existed from the observations of this study suggesting that fungal alization of the organic material during winter, spring and summer con­ trolled the peak abundance of fungi observed during the fall. Fungi appeared to be short-lived in the STOCS sediments where available carbon was the limiting factor. Over half of the benthic fungi tested were able to assimilate South Louisiana crude oil to overcome carbon limitation. Since organic carbon, and not nitrogen or phosphorus, limited fungal abundance in the STOCS it is reasonable to presume that at ecosystem, least some fungal oxidation of intrusive petroleum would occur anywhere in the area. Greater activity, however, would be expected inshore in coarse sediments subject to high nutrient freshwater outwash. Marine Bacteria from 4.6 5 Aerobic heterotrophic bacteria ranged x to 1.3 x 10/ml wet sediment. of variance indicated a (P < 0.01) Analysis significant seasonal difference in benthic bacterial populations with highest numbers during spring and lowest during winter (Table 13). There was no signifi­ cant difference between transects. There was, however, a significant difference between stations, with highest populations at Station 1, decreasing with increasing depth (Figure 33). Mean populations of ben­ thic bacteria at Stations 1, 2 and 3 (all transects and seasons) were 5 The variation 7.9, 4.3 and 2.2 x 10 /ml wet sediment, respectively. by station accounted for 47% of the total variance in benthic bacteria. The only deviation from this distribution was on Transect IV, 1977 1S.D. x 10^ x 10* x 10 10* 10 J x 10 J DURING + 28.0 41.6 31.2 3.8 x 5.1 x 35.8 0.5 0.4 6.1 SHELF Mean 40.2 + 55.4 + 47.8 + 2.7 + 3.1 + 23.5 + 0.6 + 0.5 + 4.8 + CONTINENTAL OUTER Samples TEXAS of 24 24 24 24 24 24 24 24 24 13 SOUTH Number TABLE THE OF POPULATIONS Season Winter Spring Fall Winter Spring Fall Winter Spring Fall BACTERIAL wet wet SUMMARY OF BENTHIC Type Aerobic heterotrophic bacteria (number/ml sediment) Hydrocarbon degrading bacteria (number/ml sediment) Percent hydrocarbon degrading bacteria depth. bottom and sediment of bacteria terotroplilc e h aerobic between Relation 33. Figure spring and fall. Rates of organic carbon input to the sediments during the spring are expected to be greater than at any other time during the year because of peak productivity measures in the overlying water column. Benthic bac­ teria to appear to have responded this high input during the spring, since this is the period of maximal populations. Temperature may also effect the seasonal distribution of benthic bacteria. Benthic bacterial popula­ tions were lowest during the winter, corresponding to seasonal low sedi­ ment temperatures. Hydrocarbon degrading bacteria were isolated from all 72 samples 1 collected during the study. Populations ranged from 8.0 x 10 to 1.1 x 5 10/ml sediment and were significantly correlated with total alkanes of the sediment (Figure 34), Analysis of variance demonstrated a signifi­ cant (P < 0.01) seasonal variation in the number of hydrocarbon degrading bacteria, with highest populations during fall and lowest during winter < (Table 13). There was a significant (P 0.01) difference between tran­ sects, with greatest concentrations on Transect I during winter and spring, and on Transect IV during fall. Hydrocarbon degrading bacteria were also significantly (P < 0.01) greater at Station 1, decreasing with increasing depth. The mean number of hydrocarbon degrading bacteria at Stations 1, 3 2 and 3 (all transects and seasons) was 17.3, 9.3, and 2.6 x 10 /ml wet sediment, respectively. Benthic bacteria are capable of degrading all n-alkanes from C to lt+ C 32 , but exhibit a preference for the lower ranged high-molecular-weight hydrocarbons (C ll* to C2O). Spatial variations in biodegradation of oil were examined for each season. No significant spatial variations occurred alkanes. total and sediment of bacteria degrading oil of number between Relation 34. Figure < (from 0 to 16.78%). During the spring, there were significantly (P 0.01) higher biodegradation potentials at Station 1, decreasing with increasing station number, or increasing depth. There was also a significant (P < 0.05) difference between transects, with lowest potentials on Transect 111. During the fall, there was no significant spatial variations in bio­ the degradation potential. The mean percent biodegradation of oil during spring and fall was significantly correlated with the mean number of hydro­ == carbon degrading bacteria (r 0.66 and 4 0.73, respectively). Oil significantly (P < 0.01) stimulated the growth of total aerobic heterotrophic bacteria at the majority of stations during the three sea­ sons, Growth stimulation by SLCO occurred after one week and continued Significant growth inhibition by oil was not observed through eight weeks. The number of hydrocarbon degrading bacteria of sediment was also signifi­ < cantly (P 0.05) increased by the addition of oil. Stimulation of hydro­ carbon degrading bacteria by oil was recorded after two days and continued through eight weeks. In conclusion, two study findings suggest that hydrocarbon degrading bacteria may be a useful indicator of sediment hydrocarbons in the STOCS area: 1) the number and percent hydrocarbon degrading bacteria were sig­ nificantly correlated with total alkanes of the sediment; and 2) the addi­ tion of oil to the sediment increased the number and percent hydrocarbon degrading bacteria after two days. Meiofauna The meiofauna has been largely ignored until the last three decades. fisheries and The importance of the economic aspects of macrobenthos to the function of microorganisms in converting organic material into usable in a food chain have received energy the majority of research attention, the former to a considerable extent. Meiobenthic work has, until recently, been confined to species composition, diversity and density studies, or on detailed examination of a particular group. In the last ten years increasing attention has been focused on the ecology of the marine meio­ benthos and its trophic interactions. "Meiobenthos" was first used by Mare (1942) to characterize benthic fauna of intermediate size, such as small Crustacea, small polychaetes and lamellibranchs, nematodes and foraminifera. The distinction was to separate the intermediate-sized metazoans from larger macrofauna of the bottom and the microbenthos—protozoa (excluding foraminifera), diatoms, and bacteria. as This arbitrary size definition, usually accepted animals which pass through a 0.5 mm sieve but are retained on a sieve with mesh smaller than 0.1 mm (Coull, 1973), may include representatives of the young of the macrofauna (temporary meiobenthos) but are more commonly accepted only in terms of species which even at the adult stage fit into the stated size and fit certain taxonomic categories, the permanent meio­ benthos (Mclntyre, 1969), The meiobenthos designation is considered purely statistical (Mclntyre, 1969) with no clear cut distinction between the macro-and meiofaunal a more components. Further delineation as "permanent" however, provides operational definition in terms of sampling methods and a natural grouping with certain biological characteristics (Mclntyre, 1969) Mclntyre (.1969) , further defined meiofauna as an "assemblage of small metazoans which differ from their larger counterparts (macrofauna) in their reproductive capacity as well as in the niche they fill." and general metabolism, ecological It has been suggested that the two components may: 1) compete with each other action between each other; 3) or operate independently of each other while being controlled by different environmental factors (Mclntyre, 1974). Study into the trophic relations and microecology of meiofauna indicates that they are as intricately entrenched in the integrated marine food web as the macrofauna and differ in activities and requirements. During both 1976 and 1977 meiofaunal populations diminished with increasing depth on the Texas shelf (Figure 35A-D) Consistently Tran­ . sect IV supported the highest populations inshore and Transect II the lowest. Populations of the deepest station of Transect II were almost as great as those of the shallowest station. In contrast, for the other three transects, populations of the deepest stations were only a small percentage of those of the shallowest stations. Pequegnat and Sikora (1977) reported that sampling on a monthly basis was necessary to define temporal variability of meiofaunal populations. This was best shown by nematodes on Transect 11, which was the only tran­ sect sampled more than three times during the year (Figure 36). There were population peaks in March, July-August, and November. Population peaks were much greater inshore than offshore. Figure 36 also shows that the March 1976 Inshore population was very small and November was large, followed by a very large March 1977 population and a reduced November population. Nematodes were the most abundant meiofaunal taxa observed averaging 92.6% of the total abundance of meiofauna (Table 14). Tran- the permanent sect II for the year 1976, averaged 86.9% nematodes and was the only case of a transect averaging less than 90% in the two years. The numeri­ cally dominant nematodes are listed in Table 14, Sabatzevza occurred Figure 35. Distribution of permanent meiofauna on Transects I through IV during the winter, spring and fall sampling periods by depth zone for 1976 and 1977. Points are means of populations for three seasonal sampling periods plotted logarithmically. Depth zones are; A (0-30 m); B (30-60 m); C (60-90 m); D (90­120 m); E (> 120 m). Figure 36. Monthly distribution of Nematoda at inshore stations (1 and 4), mid-depth stations (2 and 5) and offshore stations (6 and 3) of Transect II during 1976 (A)_ and 1977 (B). A californiensis sp. FOR cristate STATIONS RANGES gracilis setigera helgicae delta cerruti tentaculata 0.0 0.0 0.0 - 4.6 4.1 4.3 5.4 Polychaeta ALL AND 25.0 16.3 sura 16.7 AT ABUNDANCE. Paraonis TharyxMediomastus Aedicira Protodorvillea Aricidea SigambraPrionospio MEIOFAUNA PERCENTAGES NUMERICAL Cos OF 0.0 0.0 0.0 0.4 0.6 0.5 0.6 THE ORDER ­ 3.1 7.3 3.3 TRUE MEIOFAUNA. Kinorhyncha Eohinoderes Pyonophyes Semnoderes Traohydemus Centroderes OF IN Protozoa TOTAL PERCENT LISTED and OF IS ARE 14 MEAN erida 0.0 0.0 0.0 sopera ARE SHOWN GENERA - - TABLE 3.1 4.1 3.6 8.5 sohi SHOWN Harpacticoid Halo Enhydrosoma Pseudohradya Ameira Eotinosoma TyphlamphiasousRobertgurneya Haleotinosoma Thompsonula ApodopsyllusLeptopsyllus Stenhelia -Forarainif 25.7 15.4 36.0 PERCENTAGE COMBINED.NUMBERS excluding THE - 1977 WHERE lingia. Ilus 61.6 55.9 ella 40.9 AND Melofauna MEIOBENTHOS 1976 Nematoda 94.5 90.7 92.6 Sabatieria Halalaimus Dorylaimopsis Neotonchus Tersche Visoosia Laimella Ptyoholaime 84.1 POLYCHAETA, 100.0 100.0 Theristus I Synonchi 100.0 THE FOR Total ARE OF of (%) are TAXA THE BANKS (%) (%) (%) (%) Species Years) FOR MAJOR BOTH Mean Range Mean Range Mean (Both (%) or EXCEPT Years (%)Transects 1976 1977 Both Genera Banks Mean Range J • ( of water Laimella also occurred primarily in sandier sediments. There was a marked increase in nematodes when the sand content of the sediment was 60% or more by weight. The high percentage of nematodes in the samples was comparable to that found in muddy continental shelf areas in the Kerguelen Islands (deßovee and Soyer, 1977), off Massachusetts (Wigley and Mclntyre, 1964) and also to Wieser's (1960) 18 m mud station in Buzzards' Bay, Mas­ sachusetts . The second most abundant taxon in the STOCS study was Harpacticoida. Harpacticoid populations were proportionately much smaller than those of the nematodes (Table 14). Inversely to that of the nematodes, the pro­ portion of harpacticoids was somewhat higher at Hospital Rock and Southern Bank, averaging 8.5% of the permanent meiofauna for both banks together over 1976 and 1977. The high percentage of harpacticoids may have been more a result of very reduced total meiofauna populations at those sta­ tions, thereby increasing the proportional effect of an occasional occur­ rence, rather than a true indication of increased harpacticoid abundance. Numbers of harpacticoids taken at the transect stations ranged from 0 to 2 97.4 individuals per 10 cm in 1976 and from 0 to 59.3 individuals per 10 cm2 in 1977. The mean for all stations was 662.0 individuals in 1976 and 458.7 individuals in 1977. about 0.5% of the taxa Kinorhyncha were not very abundant averaging over all transect stations for both (Table 14). They were less even years abundant at the two bank stations with a total of 27 kinorhynchs from all stations and sampling periods in 1976 and 24 in 1977. Polychaeta was the second most abundant taxon of the total meio­ fauna (excluding the Foraminiferida and Protozoa) on Transects I through IV (Table 14), totaling 3593 individuals collected over the two years of Polychaeta highest abundances were in the shallow zone (0 to 30 meters), with numbers decreasing at the offshore stations. Abundances ranged from 2 to 115.9 individuals per 10 cm with a mean of 7.0 individuals per 2 2 10 cm in 1976 and from 0 to 47.6 individuals per 10 cm with a mean of 5.8 per 10 cm in 1977. Numbers of polychaetes averaged less for the bank stations than for the transects. Meiofauna in general are similar to macrofauna in that they not are of the a homogeneous group. They employ many same varied feeding mecha­ nisms as the heterotrophic macrofauna; subsurface specialized deposit feeders, microbial consumers, non-selective subsurface deposit feeders, and predators (Gerlach, 1978; Mclntyre, 1964). Still others are highly specialized and physiologically adapted, such as in a sulfide community where the dominant forms are ciliates and a few metazoans capable of existing in a reducing environment by employing surface existence or a narrow vertical very range (Coull, 1973). Meiofauna share similar habitats with macrofauna, both being found in all marine ecosystems, estuaries, sandy beaches, subtidal muds and the deep sea. Macrofauna show a pattern of distribution similar to that of the meiofauna influenced primarily by sediment parameters (Wieser, 1960) with preference for sandy or silty sediment. In contrast, life histories of meiobenthos are very diversified, probably not less than in different macrofauna (Gerlach, 1971). With constant numbers spawning all year in some habitats and not restricted by the resultant productivity season, may equal or excel that of macrofauna (Mclntyre, 1964). Infauna Since Petersen (1913, 1918), investigators have delineated benthic communities in relation to environmental parameters such as hydrological variables (Molander, 1928), physical properties of the bottom sediments interactions (Jones, 1950) and biological adaptations derived from species in relatively stable environments (Sanders, 1968). Community distribu­ tions have been examined in a number of different aquatic environments in recent These studies have found that the benthos varies con- years. siderably in space due to the general heterogeneity of aquatic systems and the tendency towards patchiness in the benthic fauna. The development of a large multidisciplinary research program in a little studied subtropical area of the Gulf of Mexico off the south Texas coast provided the opportunity to contrast benthic community structure and factors influencing this structure with other continental shelf eco­ systems. The south Texas shelf is comprised of much siltier, less stable sediments than other shelves such as the Middle Atlantic region which is characterized by sandier sediments out to greater depths on the shelf (Boesch, 1978). The outer Texas shelf can also be considered a true soft-bottom environment because unlike other shelves of the eastern and southern Gulf, south Atlantic or Pacific, there are very few reef areas or extensive banks with their influential biogeographic effects, £.O, '"islands in a sea of mud". Additionally, with pressure of extensive energy exploi­ tation slated for the near future on the south Texas shelf, it is imperative to document the species assemblages of the benthos in a relatively pris­ tine habitat* Although pristine, this habitat is one which would probably be most directly impacted should a major environmental disturbance occur . many of the regional fisheries such as shrimp. Ordination analysis of the infaunal species composition for each of the 25 collection sites indicated that 73% of the total variation between sites was accounted for by the first and second coordinates. The third coordinate only accounted for an additional 4% variation and showed no meaningful trends. Therefore, all emphasis was placed on the first two coordinates (X and Y axes). In order to objectively define community differences within the col­ lection sites and station scores from community ordination were evaluated by the Least Significant Difference (LSD) multiple range test. Both coordinate mean scores of the six collection periods were compared for each station. The results showed that the first ordination coordinate < was able to significantly delineate (P 0.05) four station groupings, Groups I, 11, 111 and V (Figure 37). Station Group I consisted of Sta­ tions 4/1 and 1/IV while Group II was composed of collections from Sta­ tions 4/111 and 4/IV. Station Group 111 (Figure 37) was defined by the largest number of collection sites and included mid-depth stations. According to the LSD results for the second ordination coordinate three collection sites on Transect IV (P < 0.05) differed from the other sites in significantly Station Group 111 and were thus considered a group within themselves (Station Group IV). Station Group V was comprised of the five deepest stations that showed consistently low scores for both the first and second ordination coordinates (Figures 37), A group of five stations including 5/1, 6/1, 5/11, 6/11, 2/111 did not show a significant difference from most sites in Station Group 111 or V according first coordinate mean to and were not further differentiated by the second coordinate. Therefore, 125 1 1 \y 6/111,7/12 2/m 12 \ 6/n, STATIONS 5/12 3/12 STATIONS \\ i/n,4/n 5/m, 5/n, 4/12 i/ra, 6/12, 3/11,3/in. 6/1, ,1/12 2/i, # INCLUSIVE 4/1 4/m, 2/n, 2/12, 3/1, TRANSITION 5/1, / In\ , i/i \ / I >i x/ // 6 * GROUP1IIm “ 21 / X 1 / / / COORDINATE / /\ /l FIRST 4 * / / /) /~\]/ / // * a / * */w/vuy / / / /v/ /* /* * V * ¦ * * * * •; ** y * ‘* * A A 1­ 64~2 0­ LlI h*H CO •H M CO > rH CO •H 3 3 1 o •H g 3 m o «w CO ¦u •H rH 3O o cO CO H 3 CO co a CD 3 g CO aa 33 OO 5-i U ao ao 33 oo •H *H u u 33 ¦u u CO 3 rH 3 )-i 3 bO •H a from the deep stations (Groups V). The sand/mud ratio was further able to differentiate Station Groups I and II from each other. On the second discriminant function (Figure 40A) sediment grain size deviation further distinguished differences between Groups I and II (Fig­ ure 41) as well as showing a more subtle but significant split between Groups 111 and IV. The sediment variable, percent silt, however, showed the strongest differentiation between the latter groups. The third discriminant function (Figure 40B) was also significant < (P 0.05) and accounted for an additional four percent in variation between station groups. This function further illustrated the discrimi­ silt 111 and nating power of percent in not only differentiating Groups IV from the transition stations which were in the same IV but also Group general depth range (Figure 41). The overall chi-square derived from the general Mahalanobis distance squared was 640.9 for the discriminant analysis of station groups accord­ ing to environmental variables. This chi-square was highly significant (P < 0.001) and suggested that the null hypothesis of no environmental difference between groups be rejected. It was assumed, therefore, that there was very little probability the station groups could have been formed by chance but that the separation between them was real. These results confirmed the biological model and suggested some of the variables potentially influential in structuring the infaunal communities along the shelf depth gradient. of to Sediment properties appeared be relatively important in terms community structure patterns according to Figures 40 and 41. Although these properties are mildly correlated with water depth, the most power­ ful discriminating variable observed, there are other factors also depth be considered in the interpretation of results from the study. These factors include the degree of food avail­ ability to the benthos and bottom water environmental variability along the depth gradient as characterized by surface chlorophyll concentrations and the standard deviation measure of temperature and salinity. Data presented in previous chapters indicate that these variables decrease with increasing water depth on the shelf. Chlorophyll concentrations were highest and also most variable in shallower waters (Chapter 3) where high­ est densities of infauna were observed. Lower concentrations of primary producers, whose abundances were less variable throughout the study inter­ val at deeper stations, were associated with lower densities of infauna and more evenly distributed population numbers (equitability) within these assemblages (Figure 38). Temperature and salinity were both most variable at the shallower water collection sites, with decreasing variability as depth increased (Chapter 2). implied that the shallower benthic habitat was much This more variable and less predictable in terms of environmental changes and, therefore, conducive to dominance by a few fauna. This variability of the shallow shelf was further verified by the fluctuations of chlorophyll representing a food source to the benthos through the detrital pool. In addition to the influential effects of certain sediment characteristics on benthic community structure, gradational features of a food source to the benthos and variability in the bottom water environment were also suspect in potentially causing the different faunal patterns observed. Other benthic marine systems investigated have been shown to be typically gradational in space with respect to sediment and other environ­ mental variables (e.g, Day et at,, 1971; Field, 1971; Boesch, 1973; changes in macroinfaunal communities. to the observations According pre­ sented above, sediment structure plays an important role in structuring the benthos. Superimposed on the mechanics that the substrate pose on the benthic infauna, however, are factors involved in producing variability both to a food source of the benthos and the overlying hydrologic environ­ ment. These environmental aspects couple together to produce a very com­ plex association between the Gulf of Mexico benthos and the habitat in which they live. According to Glemarec (1973), nature of the sediments is of prime importance for the settlement of most invertebrate larvae and the resul­ tant composition of communities. He extends his definition of spatial stages of the benthos, however, to include the effects of variations in bottom water temperature and cites examples from Jones (1950) and Lie (1967). Glemarec concludes that the environmental properties which permit a distinction between faunal assemblages are different depending upon are or whether the assemblages in shallow deep water. Significant variability in shallow waters combines with coarse ill- sorted sediments to provide an unstable habitat. This habitat is charac­ terized by many different fauna with few exhibiting dominant abundance (low evenness). another habitat also with coarse sediments In contrast, (Station Group IV) exhibits the most diverse fauna observed during the study period. These sites, in addition to having a very heterogenous sediment structure, are characterized by very stable hydrologic variables as well as a more predictable food source. As Sanders (1968) and McCall (1977) illustrated, in a marine habitat subjected to continual local disturbances and harshness of environmental variables as found in Texas inner-shelf waters, a few highly specialized in large numbers. These species are able to invade new areas voided of fauna by a local disturbance (i.e. currents) and maintain their large pop­ ulation sizes because of the abundant food sources of and unpredictability the bottom water environment including occasional disturbance from storm currents. In contrast, deeper shelf habitats exhibit less bottom water variability, and sediment characteristics become the key to faunal distri­ bution. This is evident in the faunal changes between the mid-depth sta­ tions (Group III) where the silt content is high and the deep water sta­ tions where clay is the more dominant sediment component. There was a variable sand/silt/clay mid-shelf mixture observed at m most stations between water depths of 20 and 50 (Station Group III) with silt representing the dominant component. These stations generally showed a sand/mud ratio of 0.3 to 0.5, much lower than the shallow study sites. Percent silt was also a major discriminating variable separating Station Groups 111 and IV (Figure 41). Group 111 exhibited the lowest number of infaunal species on the shelf while supporting population densities second only to the shallow sites. Associated with these community parameters were low measures for both species diversity and equitability suggesting that these species assemblages were dominated by a few fauna with high densities. Rhoads (1974) stated that siltier sediments present a difficult environment to which fewer species can adapt. Not only are the ecological niches decreased by a more homogenous substrata (Ward, 1975) but the sta­ bility of particle sizes to bottom water currents is less. This can pro­ duce a relatively unstable substrate for infauna inhabitants. A good example of the instability of this particular area is the sediment resus­ pension associated with the nepheloid layer that occurs frequently during the year (Kamykowski et at., 1977). Although the results of this investigation were similar to other studies cited above in that a gradational nature was defined for the Texas shelf benthos related to several environmental variables, differ­ ences between some of these variables in this and other studies was the key. As stated earlier, the Texas shelf differs from other shelf ecosys­ tems because of the silty nature of its sediments. The infaunal-environ­ mental relationships observed here suggest that these siltier sediments may be responsible for a difference in dominant taxa on the Texas shelf compared to other shelves such as the Middle Atlantic. Polychaetes were the dominant taxa observed in this study. The majority of their feeding strategies, according to comparisons with the fauna discussed by Fauchald and Jumars (in press), involved deposit feed­ ing modes. These strategies are much more conducive to silty, unstable bottom habitats (Sanders, 1960; Saila, 1976). In contrast, the dominant fauna observed on the Middle Atlantic shelf were amphipods (Boesch, 1978) This shelf is characterized by sandier sediments than the Texas shelf. Amphipods derive their nutrition primarily by suspension feeding, which according to Sanders (1960) and Levinton (1972), is a more appropriate feeding strategy for sandier more stable sediments. It was concluded Texas shelf showed infaunal that the subtropical consistent with other shelf ecosystems in terms of environmental patterns gradation (Day et al., 1971) and shallow water variability as found in temperate marine systems (Sanders, 1968). The Texas shelf differed, how- in from at least one other shelf extensively studied (Boesch, 1978) ever, that a different taxa dominated the infauna and this difference was pos­ sibly related to structure differences of the mid-shelf habi the sediment tat between the two areas. Epifauna Northern Gulf of Mexico epifauna are considered by many investigators as an extension of the Carolinian province with faunal divisions at the Mexican border and just east of the Mississippi delta (Hedgpeth, 1953). The STOCS study area falls within the Texas to Mississippi delta region, but by virtue of the southernmost stations, is influenced by Caribbean fauna. Distribution of any species is based on a complex of environmental factors Temperature and salinity control the range of benthic species, but within that range, more subtle factors determine faunal distribution. Depth was the most apparent factor controlling epifaunal distribution in this study. The results of cluster analysis, which were used to define community changes for epifauna on the Texas shelf, were relatively similar for both 1976 and 1977. The analyses divided the shelf into two major regions based on depth and/or distance from shore (Figure 42), All stations within 10 to 45 m depth (plus 2/II at 49 m) and located less than 30 miles off­ shore were grouped together (A). Stations with depths greater than 45 m and located at least 30 miles offshore formed the othermajor group (B). The two regions varied in other physical variables. Bottom water tempera­ 37 the tures (10 to 29°C) and salinity (30 to ppt) varied widely throughout B stations were characterized by a more stable year in Group A. Group temperature (15 to 25°C) and salinity (35 to 37 ppt) regime. There was considerable overlap of sediment types between the two regions but the sandiest sediments were found at shallow, nearshore stations and the high­ est clay content was in sediments from the deep offshore stations. Subdivisions from cluster analysis divided the study area into six stations groups of (Figure 42). These minor divisions generally corres­ ponded to shallow (10 to 15 m), shallow-intermediate (22 to 45 m), deep- intermediate (47 to 100 m), and deep (106 to 134 m) stations. Stations Figure 42. Location of Station groups fromcluster analysis of seasonal epifaunal data. Seasonal changes in abundance and group. the mobility of epifaunal organ­ isms precluded clean distinctions of station groups consistent throughout the year. Station groups were also defined by the species found there. Clus­ tering by species or inverse analysis resulted in eight species groups (Figure 43). The first three groups of species were collected only at stations with greater than 45 m depth; Species Group IV was taken most consistently at the same stations. Group V species were collected at intermediate depth stations but not at shallow or stations. Species deep in Groups VI and VII were most often collected at stations less than 45 m in depth. Group VIII species were collected at all but the deepest sta­ tions. Although a species group was relatively constant to a station group, most individual species responded in a unique way to the physical environment common to the stations. For example, many of the species most characteristic of the shallow shelf are motile decapods found in inlets, bays and shoal areas in summer and early fall. Copeland (1965) collected large numbers of Traahypenaeus S'im'ttis and Squitta empusa in Aransas Pass Inlet in late summer and early fall. Large numbers of Penaeus setiferns are found in the bays in fall and support a sizable bay fishery. Seasonal changes in population may be related to the annual temperature (14 to 29°C in 1976) and salinity (31 to 36 ppt in 1976) extremes at inner-shelf stations. In contrast, large numbers of species with low abundance characterize the outer-shelf assem­ blage. High equitability and species richness of this area reflect the relatively stable environment conditions characteristic of the area. Similar to the general community structure differences on the Texas numerals Roman data, epifaunal seasonal of analysis inverse from dendrogram Species 43, Figure species-groups. to refer consistent over shelf being relatively two years of study, specific com­ munity variablessuch as number of species, density, diversity and equita­ bility showed similar trends across the shelf between years (Figures 44 through 46). Number of epifaunal species collected per station presented no consistent general pattern. The numbers collected were much smaller than in the infaunal collections. Along Transect I, epifaunal species numbers were fairly evenly distributed during each collection period. Differences between seasons were apparent. The winter sampling showed fewer species collected on this transect. The number of species collected at 5/1 was at all collection times. Transect II showed somewhat depressed a varying pattern of species abundance spatially and temporally. The winter collection had a peak species abundance at 6/II suggesting an increase with depth. There were species abundance peaks at Station 2/II in both spring and fall collections so that the abundance of species was greatest at mid-depth and decreased shoreward and offshore. On Transect 111, there was a slight winter increase in species richness with depth. Spring collections at the deepest two stations (3 and 6) were extremely depressed. Minor peaks in species abundance occurred at Stations l/111 and 2/111 in the fall. Transect IV epifaunal species richness varied widely with season. The winter collection showed a strong decrease in species richness with depth. In spring numbers of species were somewhat evenly distributed along the transect with Station 6/IV somewhat depressed The fall collection exhibited a strong positive correlation of species richness with water depth. The number of individual epifaunal organisms collected at each sta­ tion generally peaked at mid-depth or shallow-intermediate depths and decreased shoreward and offshore (Figures 44 through 46). Transect I Figure 44, Shannon diversity values -H", equitability -E, number of species and number of individuals for winter 1977 epifaunal data. - Figure 45. Shannon diversity values H", equitability -E, number of species and number of individuals for spring 1977 epifaunal data. - Figure 46. Shannon diversity values H", equitability -E, number of species and number of individuals for fall 1977 epifaunal data. with maximal numbers of individuals at inshore sites, more so than other transects, A highly varied pattern of density was on Transect 11. seen Winter collections were small and similar in numbers of individuals across the shelf. A major peak in density occurred in the spring collection at Station 2/II with numbers of individuals decreasing shoreward and offshore The fall collection on this transect displayed the densest epifaunal com­ munities observed for the entire year, particularly at the four shallowest stations. The number of epifaunal organisms collected on Transect II varied widely through the year. Dense populations on the inner half of the study area occurred in the winter collection. Densities along this transect were low during collection period. Fall collections the spring indicated peaks of abundances at Stations 1, 2 and 6. Epifaunal density patterns on Transect IV were similar to Transect 111 with the winter onshore collections slightly diminished and the fall collections generally increased. Epifaunal diversity (H 1 ) was generally lower than that exhibited by infaunal collections (Figures 44 through 46). No general pattern of diver sity across all transects was observed. Relatively high densities were consistent across the shelf for Transect I with some to increase tendency with depth in the winter with a major peak at Station 2/II in the spring and a major decline at Station 3/II in the fall. Transect 111 exhibited a fairly high winter diversity with a minimum at Station l/111. Increases in this variable with depth were observed, except at the deepest site where there was a decrease in diversity. A major decrease in diversity was observed at 3/111 in the spring collection. Diversity on Transect 111 in the spring was fairly uniform with decreases at Stations 5 and 6. There were relatively low diversities on Transect IV in the winter, uniformly high values in spring with the exception of Station3/IV and a of H* tendency values to increase with depth in the fall. Epifaunal equitability values showed no pattern consistent to all transects (Figures 44 through 46). There was a trend toward greater equi- A tability inshore and offshore with mid-depth areas being depressed. of smooth pattern increasing equitability with depth in the winter was evident on Transect I. Spring and fall values were more diverse with low equitability at Stations 1 and 6 in the spring and Stations 4,2, and 3 in the fall. Transect II exhibited increased at equitability the deep­ est site (Station 3) in winter and spring which decreased sharply in fall concommitant with an increase in equitability at the nearshore stations. Transects 111 and IV were similar very in the winter with high equitability at all except the shallow mid-depth stations. Equitability on Transect 111 showed peaks shallow and deep with variable levels between in the spring while Transect IV values remained almost uniformly high. Fall collections on Transects 111 and IV indicated the trend toward greater equitability inshore and offshore with decreased values at mid-depths. As illustrated above, epifaunal community structure parameters showed no general trends or spatial patterns. Variation in temporal and spatial abundances of dominant species in 1976 was due to recruitment of age classes at shallow to shallow-intermediate stations, as well as young to migration of the adult population, accompanied by reduction in abun­ dance, to the deeper stations. The same pattern was observed in 1977 that there was a for the abundance to be concen­ except stronger tendency trated at stations along Transects I and 11. Because epifaunal species differ in physical and biological needs and some are capable of moving considerable distances, analysis of indi­ vidual species distributions may be the best method for interpreting the shelf ecosystem in terms of numbers and kinds of species. Further infor­ mation that can be derived from the data includes an understanding of the distribution of species important to man (directly or indirectly) and the identification of species with narrow or critical tolerances to environ­ mental change. Demersal Fish Patterns of distribution and abundance of outer continental shelf fishes off the Texas coast have been examined by a number of workers {e.g, Hildebrand, 1954; Chittenden and Moore, 1977), but ecological aspects of this ichthyofauna (particularly regarding factors which affect these patterns) remain poorly understood. Although distributions of certain species off Texas and in other parts of the Gulf of Mexico have been related in a broad manner to a few obvious factors such as depth, sediment and Chittenden and and temperature (Dawson, 1964; McEachran, 1976; Lewis Yerger, 1976), a more detailed exposition of the relationship between fish populations and the ecological factors which affect them is desirable. The need for statistical evaluations of these fish-environment relationships has been specifically pointed out (Chittenden and Moore, 1977), The numerical analyses of the demersal fish data are in presented Figure 47 and show three distinct station groups aligned with depth on the shelf. The following general conclusions were from the anal- apparent yses: 1) zonation appeared to be depth related, with temperatureselated seasonal migration patterns influencing the species associations; 2) the shallow-shelf turbulent zone exhibited low species diversity throughout the year, with especially high numbers of individuals in winter and spring; 3) the nearshore faunal associations dissipated during the late Figure 47. Station groupings for demersal fish according to cluster analysis. Numbers in parentheses are depths in meters. and deep-water associations were somewhat more stable throughout the year with the mid-shelf groups of species having the highest diversity; 5) north-south gradients were minimal except during autumn when weak species associations developed to show that the northern two transects were slightly different from the southern evidence of two transects; and 6) there was considerable species "shuffling" during the year in all faunal zones, which suggested that Petersen-type, species-dominated communities did not persist in the shelf areas that were studied. Over 160 fish species were captured during the three years of sam­ pling, but only 57 species were captured in excess of 100 individuals and 22 species in excess of 1000. The most common species are listed in Table 16, and their frequencies of occurrence among the ten most abundant species for each season and station group (defined by Figure 47) are given in Tables 17 and 18. Most of the common species were dominant elements the two . (*i.eamong the top ten species) of ichthyofauna in only one or station groups (:e.gSyaoium gunteviDigleotvum bivittatum in Station . 3 Groups 1 and 2; Sevvanus atvobranchus in Station Groups 2 and 3), reflect- the spatial (depthwise) differences in the fish assemblages found over ing the study area. The notable exception was Tvaohurus lathcani, which was dominant at in all three station Sea- roughly equal frequencies groups. sonal changes in the extent to which species dominated the ichthyofauna . also occurred (e.gSyaoium guntevi was predominant mainly in winter and fall), although a number of species showed no variation (e.g. Stenotomus capvinus, Sevvanus atvobranohus ; Table 17). A greater number of species were caught in night trawls than in day trawls during the seasonal sampling cruises. Part of this difference was TABLE 16 TOTAL ABUNDANCE AND NUMBER OF OCCURRENCES (NUMBER OF TRAWLS IN WHICH TAKEN) OF THE MOST ABUNDANT FISHES CAPTURED DURING THE SAMPLING PROGRAM, 1974-1977 Number of Individuals Number, of Occurrences Species Trachurus latharrrl 8612 243 Serranus atrobranchus 8406 365 Micropogon undulatus 7767 140 PepriZus burti 6656 169 Cynoscion nothus 5952 123 Syaaium gunteri 4465 263 Stenoterms caprinus 3905 327 Pristipomoides aquiZonaris 3534 312 Prionotus paraZatus 2608 235 PoZydactyZus octonemus 2392 65 Saurida brasiZiensis 2162 194 Anohoa hepsetus 1987 59 ChZoroscombrus chrysurus 1945 65 Sphoeraides parvus 1724 163 1724 217 Upeneus parvus 1705 297 Centropristis phiZadeZphioa Prionotus stearnsi 1635 187 Cynoscion arenarius 1431 130 Prionotus rubio 1429 217 1390 193 Synodus fastens Triahopsetta ventraZis 1186 308 DipZectrwn bivittatum 1072 133 Porichthys porosissimus 957 189 Pontinus Zongispinis 548 73 Synodus poeyi 512 112 BoZZmannia communis 507 112 Lepophidium graeZZsi 455 149 17 • TABLE FREQUENCY OF OCCURRENCE OF COMMON FISHES AMONG THE TEN MOST ABUNDANT SPECIES DURING EACH SEASON. EACH OCCURRENCE CORRESPONDED TO A SINGLE SAMPLING SERIES (E.G. STATION GROUP l-DAY-1977). A TOTAL OF 12 OCCURRENCES (SAMPLING SERIES) PER SEASON WAS POSSIBLE. SAMPLING SERIES INCLUDED: STATION GROUPS 1977 1,2, 3/DAY,NIGHT/1976, (DATA FROM WOHLSCHLAG 1977, 1978). Number WINTER SPRING FALL Species of Occurrences Among Top Ten Species Anohoa hepsetus 2 3 1 Cynoscion nothus 3 3 3 46 Mvcropogon undulatus 3 Peprilus burti 3 6 3 Syaadum gunteri 8 37 Cynosoion arenarius 4 3 1 Sphoeroides parvus 4 34 Trackurus lathami 2 8 6 Polydaatylus octonemus 4 6 - - Chloroscombrus ohrysurus 3 3 4 74 Upeneus parvus Stenotomus aaprinus 8 8 9 Ddptectrum bvvittatum 2 1 6 Saurida brasvliensis 3 2 2 Serranus atrobranakus 8 8 8 Synodus fastens 2 31 PrConotus stearnsi 2 3 5 Pristipomoides aquvlonaris 6 76 Prdonotus paralatus 4 5 5 Triohopsetta ventralis 5 34 2 13 Ealieutiahtkys aculeatus Pontirvus longnspdnvs 1 2 4 Prionotus rubio 4 1 3 Centropristis pkiZadelphioa 3 33 FREQUENCY OF OCCURRENCE OF COMMON FISHES AMONG THE TEN MOST ABUNDANT SPECIES IN EACH DEFINED STATION GROUP. EACH OCCURRENCE CORRESPONDED TO A SINGLE SAMPLING PERIOD (E.G. WINTER-DAY 1977). A TOTAL OF 12 OCCURRENCES (SAMPLING PERIODS) PER STATION GROUP WAS POSSIBLE. SAMPLING PERIODS INCLUDED: WINTER, SPRING, FALL/DAY, NIGHT/1976, 1977 (DATA FROM WOHLSCHLAG 1977, 1978) Number of Occurrences Among Top Ten Species Species Station Group Station Group Station Group 1 23 Anchoa hepsetus 6 Cynoscion nothus 8 1 - - Micropogon undulatus 11 2 4 1 Pepin,lus burti 7 9 81 Cynoscion arenarius 7 1 Syacium gunteri - - 7 4 Sphoeroides parvus Trachurus lathami 5 6 5 - Polydactylus ootonemus 7 3 Ohloroscombrus chrysvrus 5 1 - 2 58 Upeneus parvus Stenotomus coprimes 2 12 11 - 4 5 Diplectrum bivittatum - Saurida hrasiliensis 5 2 - Serranus atrohranchus 12 12 - Synodus foetens 5 1 Prionotus steamsi 8 2 — Pristipomoides aquilonaris 7 12 — 2 12 Prionotus paralatus — Trichopsetta ventralis 2 10 — 1 5 Halieutichthys aculeatus — — 7 Pontinus longispinis Prionotus ruhio 4 2 2 — Centropristis philadeIphica 2 7 However, the differences between the numbers of night and day trawls taken during the seasonal cruises were rather small, and it appeared reasonable to conclude that some biological reason existed for the observation that night trawls yielded greater numbers of species than did day trawls during both 1976 and 1977. In terms of day vs, night collections of demersal fishes, parameters such as biomass, number of species and individuals as well as measures of diversity differed throughout the year. Fish taken predominantly during day collections were commonly schooling species while predominantly noc­ turnal species were solitary in nature. Numbers of species were low in fall and high in the spring. General catch statistics illustrated that highest densities of dem­ ersal fish occurred during the day in spring and during the night in fall The lowest catches occurred in winter for both day and night. The lowest biomasses were taken during the winter for both day and night. Highest seasonal biomasses were observed during the night in fall. Spring and fall daytime collections yielded much higher biomasses than did winter. There were no obvious trends in biomass correlated with depth. The relationships between abundances of selected fish species and some physical variables were examined by plotting abundance of these species against values of a particular variable. From this exercise it was apparent that within a given species different sizes of fish may respond differently to some environmental variables. The implication is that further studies should consider the possible effects of individual size on the relations of the fish to environmental conditions. The diversity of demersal fishes was low at shallow stations and in fish populations appeared to be related to depth, temperature, and move­ ments into and out of the estuaries. Discriminant analysis, using the defined demersal fish station groups in Figure 47, was applied to data on STOCS bottom water and sedi­ ment physical variables to investigate relationships between the fish communities and their habitat. Physical variables used were bottom water temperature (°C) and salinity (%©)» sediment mean grain size (0 units), standard deviation and skewness of the sediment grain size distribution, and percent silt composition of the sediment. The analysis yielded two discriminant functions. Values for the standardized coefficients indicated that mean grain size, salinity and percent silt were the most Important variables on the first discriminant function. These three variables served most to discriminate between demersal fish station groupings on the shelf with respect to the first discriminant function. Mean grain size, skewness and standard deviation of the grain size distribution served most to separate demersal fish station groups with respect to the second discriminant function. The discriminant scores of the data cases for the three fish station groupings are plotted with respect to the first and second discriminant functions in Figure 48. Each of these groups was found to be significantly different from one another. Interpreting the patterns in terms of the the demersal fish original physical variables, group represented by of Station Group 1 was characterized (relatively) by a combination large Station mean grain size, low salinity and high percent silt composition. Group 3 had the opposite characteristics, while Station Group 2 could be characterized as intermediate between Station Groups 1 and 3. Station Figure 48. Discriminant space based on analysis of physical variables Each number represents a sampling episode (sampling sta­tion for a given time period; e.g. Station 1/1, day-winter] with value equal to stationgroupidentification. Symbol (+) denotes a group centroid. Values in parentheses by discriminating variables are standardized discriminant function coefficients (weights). values, respectively, the second discriminant function. In terms of physical variables, the demersal fish inhabitating Station Group 3 were related to a relatively small mean sediment grain size, low variation (standard deviation) in the sediment grain size distribution, and a negative skewness in this distribution. Fish occurring at Station Group 2 were related to the opposite characteristics, and Station Group 1 demersal fish chose a range of values for these physical variables intermediate between the other two groups. Discriminant analysis using fish abundances (from all sampling episodes over three years) as discriminating variables yielded two dis­ criminant functions, with the first approximately twice as important as the second in separating station groups. Standardized coefficients showed the following species to contribute most to the first discriminant function; Cynosoion nothus Pristipomoides aquilonarisSphoeroides 33 parvusSyaoium gunteri3 Triohopsetta ventralis and to a lesser degree, 3 3 Chloroscombrus ohrysurusMioropogon undulatus Peprilus burti and , ,3 Prionotus paralatus Bollmannia communis Syaoium gunteriSynodus . 33 foetens Synodus poeyi and Triohopsetta ventralis were the most important 3 for the second discriminant function. species A discriminant plot of the demersal fish station groups (Figure 49) showed Group 1 to generally have the highest scores and Group 3 the lowest on the first discriminant function. Group 1 could therefore be viewed as having, in combination, relatively high abundances of Cynosoion nothus Sphoeroides and Syaoium and low abundances of Pristipomoides 3 characteristics. and Triohopsettawhile Group 3 had the opposite Groups , 1 and 3 had roughly equal mean scores (with Group 1 slightly higher) and Figure 49. Discriminant space based on analysis of fish abundance. Fish number represents a sampling episode (sampling station for with a given time period; e.g. Station 1/1, day-winter) value equal to station group identification. Symbol (+) denotes a group centroid. Values in parentheses by dis­criminating variables are standardized discriminant func­ tion coefficient (weights). and 3 thus could be characterized as having a combination of relatively high abundances of Syaoium and Trdohopsetta and low abundances of Boll­ marmia and the two Synodus species. Group 2 showed converse features. Pairwise statistical comparisons of the group centroids (using F-values on Mahalonobis distances between groups) revealed significant differences < between all groups (P 0.001). Although the discriminant analysis using fish abundance data was aimed toward obtaining descriptions of the defined station groups with respect to the common fishes, it also provided a test of the growth of The the groupings (as did the analysis using physical variables). statistically significant differences between the groups (P < 0.001) and the moderately high proportion (0.758) of data cases correctly classified in the discriminant analysis indicated that the defined demersal fish station groups (Figure 47) could be satisfactorily differentiated on the basis of abundances of common fishes while being explained in terms of their relation to environmental factors of the benthic habitat. The work described above on demersal fishes serves to identify major components of the outer continental shelf benthic ichthyofauna and describes the more obvious spatial and temporal patterns in abundance of species. The characterization of major depth zones using common fishes of by discriminant analysis as well as by straightforward descriptions the fauna should be particularly useful for the assessment of man’-induced impacts on this environment. Benthic Biota Body Burdens Hydrocarbons The majority of the studies regarding petroleum pollution have centered on the immediate and long term effects of catastrophic events such as oil spills. This emphasis is partly due to the identifiably apparent impact of large amounts of oil in an area and partly due to the relative ease of identifying and quantifying some petroleum compounds in spill situations. The effects of low level and chronic inputs of petro­ leum have been less intensively studied and information on background levels of hydrocarbons in unpolluted environments is scarce. Although identifying and quantifying trace quantities of petroleum hydrocarbons have been major deterrents to low level studies, methods are rapidly trace being developed for hydrocarbon analyses. One of the major problems associated with quantifying trace levels of petroleum in the environment is differentiating petrolic compounds from biogenic hydrocarbons. This differentiation is complicated by the effects of weathering or environmental degradation on the hydrocarbon composition of petroleums. Unlike the case of an oil spill, where a single source of petroleum generally provides a very characteristic hydrocarbon pattern, trace levels of petroleum may be from a number of sources, such as petroleum production, or shipping and waste disposal, which further complicates hydrocarbon patterns and thus detection and quantification. The use of a number of parameters has been suggested to aid the of analyst in distinguishing sources hydrocarbons in environmental samples. One of these is the measurement of ratios of concentrations of individual hydrocarbons, such as the ratio of n-heptadecane (Cl7)/ pristane and of pristane/phytane (Ehrhardt and Blumer, 1972). These ratios have been suggested as aids in the detection of a single source of petroleum contamination as they are generally characteristic of an oil. concentrations of hydrocarbons in clams collected from various areas did not correlate with those in the sediments. Concentrations of hydrocarbons in clams were found to range from 8.5 to 11 yg/g body weight, while con­ centrations in sediments ranged from 9 to 228 yg/g. Benthic organisms collected from unpolluted deep sea areas had hydrocarbon distributions quite different from those distributions found in surrounding sediments (Teal, 1976). These reports indicate that the effect of sediment-adsorbed hydrocarbons on the hydrocarbons of benthic epifauna is quite difficult to predict. It is probable that hydrocarbons in water, including those from sediment desorption in interstitial water, have a greater effect on the hydrocarbon content of benthic organisms than those adsorbed directly from sediment. Uptake from food is also probably a more impor­ tant source of hydrocarbons than from sediment. Information on mechanisms of hydrocarbon transport in the marine environment, such as food chain transfer and uptake from water and sedi­ ment is important for assessing the probable effects of petroleum hydro­ carbons. Few studies of hydrocarbon distributions and transport, parti­ cularly in benthic organisms and the benthic environment, have been reported. Approximately 400 faunal samples from the benthic habitat, repre­ senting 48 species, were analyzed for high-molecular-weight hydrocarbons. The mean and standard deviations of selected parameters from the analyses of the six most frequently occurring species are given in Table 19. Overall, total hydrocarbon concentrations ranged from less than 0.01 yg/g (ppm) to 54.47 yg/g dry weight with the majority of samples containing the less than 1 yg/g. Pentadecane (Cl5) and heptadecane (Cl7) were CPI20-32 3.714.2 (27) 6.8+10.1 (22) 6.7+18.3 (18) 1.A10.8 (8) 10.1121.8(17) 6.218.6 (17) A 0 n*_2 18.6110. (23) 1.610.6(5) 16.017.2(28) 6.213.5 (8) 5.613.3 (16) 19.316.9(15) MOLECULAR CPI c Phytane 2.713.2 (2) 0.210.1 (2) 0.610.1 (5) 1.010.7(2) 0.910.2 (5) 2.110.8 (10) HEAVY A MACRONEKTON 18 A 17 C FROM Pristane 9.3113. (3A) 2.011.7 (17) 2.612. (3A) 3.616.0 (18) 5.913.9 (25) 33.A+37.0 (18) AND (2)PARAMETERS Pristane Phytane 166.51172.9AA.0158.0 (2) A6.7120.5 (5) 13.015.6(2) 32.8125.3 (6) 132.0165.9(10) MACROEPIFAUNA 19 OF TABLE SELECTED C25-C32 22.7128.5 (A2) 51.1139.1 (3A) 10.213.2(38) 20.9128.8 (21) 31.5126.3 (26) 17.5123.7(25) FOR 00 ANALYSES Alkanes Ci9-C 16.5118.6(A2) 9.1112.7 (3A) 7.1110.3 (38) 9.7111.8 (21) 13.3118.1(26) 13.5117.7(25) DEVIATIONS 2u of A 8 Sum 2 HYDROCARBON 1 *4“ 60.9±3A.0 (A2) 39.7±7. (3A) 82.7±26.3 (38) 69.A+32.7 (21) 55.2131. (26) 69.0+36.3 (25) 1 STANDARD C WEIGHT C .28 AND Total Alkanes Cv«g/g) 1.89+3.32(AS) 0.1A±0.28 (AS) 2.98±A (38) 0.19+0.20 (27) 1.02+1.83(27) 8.58+12.00 (25) MEANS s spp. ’ Species (Number Analyzed) Lotigo Fenaeus azteous (48) stipomoideaquilonavis(38) Serranus atrobranahus (27) Stenotomus oaprinus(27) Traohurus lathami (AS) (25) Fvi Pristane was levels. found in almost all samples at relatively high was Phytane found in approximately 20% of the samples, generally at less than 0.05 yg/g. The pristane/phytane, pristane/heptadecane and phytane/ octadecane ratios ranged widely and did not appear to be indicative of a common source of petroleum in the study area. The Carbon Preference Index (CPI) ratio illustrating odd-carbon dominance especially for the and CPI2O-32 ratios also were not indicative of con­ CPIm-20 petroleum tamination. Squalene was frequently the only compound detected in the aromatic fraction. Aromatic compounds were rarely detected and were usually at 0.005 yg/g or lower concentrations. The distribution of aromatics was not suggestive of petroleum origins. Unresolved complex mixture (UCM) peaks were also rarely detected in the gas chromographs and were very low when present. The distribution of phytane in the samples appeared to yield a spatial trend. Phytane was found most frequently at Stations 1 and 2, Transects 111 and IV. Stations 1 and 2, Transects I and II also had a higher frequency of phytane occurrence than Station 3 of all transects. Analyses of variance, testing for spatial and temporal differences, that indicated three correlations for brown shrimp (Penaeus aztecus ) to be indicators of seasonal changes in hydrocarbon distri­ appeared good butions. As can be seen in Figure 50 the hydrocarbon distribution changes with season, causing significant changes in the low and high sums of hydro == carbons (p 0.02) and the CPI 2 (p 0.01). The dominant hydrocarbons observed were pristane, pentadecane and sources heptadecane. These hydrocarbons probably reflect dietary since et dl, pristane is the major hydrocarbon in zooplankton (Blumer 1964) Figure 50~ Percent distribution of n-alkanes inFenaeus azteaus (brown shrimp). algae (Clark and Blumer, 1967). The overall concentration of hydrocarbons in the samples were generally quite low (less than 1 ]ig/g dry weight in in many samples) and the hydrocarbon distributions found were not sugges­ tive of petroleum. The CPI ratios showed the high odd-carbon dominance characteristic of biogenic hydrocarbons (Clark, 1974; Clark and Finley, 1973; Cooper and Bray, 1963) although shrimp tended to have CPlm_2o values close to 1. Phytane was the only potential indicator of petroleum (Farrington et at 1972; Blumer and Synder, 1965) found with any frequency in the ., samples. It was found most often in samples from Stations 1 and 2 of all transects. This may indicate some contamination from petroleum onshore or activities or may reflect species variation and shipping mobility, as the species collected at Stations 1 and 2 were generally different from those at Stations 3. The distribution of aromatics, when present, was not suggestive of petroleum sources. Thus, petroleum contamination of the benthic organisms of the was not during the and the data study significant study period obtained should provide an excellent data base for future studies of efforts have concentrated on petroleum pollution. The data synthesis the data for characterization maximizing the utility of purposes. The significant results for brown shrimp are indicative of a change in hydrocarbon distribution that occurs in shrimp in spring, possibly due to spawning activities or to dietary effects (Figure 50). The hydrocarbon levels in shrimp also lower in winter and fall (0.04 and 0.06 yg/g, were respectively) than in spring (0.33 yg/g), although the differences were different at p = 0.05 level. not significantly isms for monitoring the presence of petroleum hydrocarbons. Shrimp dem­ distribution with onstrate significant changes in hydrocarbon season, but these changes are relatively consistent and quantifiable. The low levels of hydrocarbons in shrimp may also simplify the detection present of pollutant hydrocarbons. A post-drilling rig monitoring sample obtained in winter had 0.6 yg/g total hydrocarbons compared to 0.04 yg/g found for the winter samples in this study. This sample also had very low CPl's (CPliif-2 o=l.l, CP 12 o —3 2 =0.6) and a distribution of hydrocarbons sugges­ to tive of petroleum, especially when compared the patterns found for shrimp in this study, as shown in Figure 51. In contrast, shrimp from an oil producing area of the Gulf had higher hydrocarbon levels (0.53 to 2.45 yg/g) than found in this study (Middleditch and Basile, 1978). Of the approximately 140 macronekton analyses performed, 120 were for two species, the red and vermilion snappers {Luteanus oampeohanus 20 were obtained . and Rhombopl'ites aurorubens) Approximately samples for each species over the two years of this study. Each sample yielded three tissue analyses: muscle, liver, gill in 1976, and gonad in 1977, which were each analyzed separately. The ranges and means of total hydrocarbon concentrations found for the macronekton are summarized in Table 20. The means of several of the parameters measured in muscle and liver are shown in Table 21. The alkanes, (Cl5) and n-pentadecane n-heptadecane (Cl7), and pristane were the major aliphatic hydrocarbons in all samples. In red snapper muscle, the Cl 5 plus the Cl 7 n-alkanes totaled 23 to 100% of the n-alkanes; the total was less than 75% in only 3 of the 20 samples. One of these samples had the C27 n-alkanes as the major n-alkane while the other two had a wide range of hydrocarbons. In 51 Figure Comparison of itig monitoring and seasonal hydrocarbon distribution in Fenaeus azteous (brown sbrimpl* Gonad 1.7-55.1 36.8131.8 2.3-25.3 6.817.2 TABLE 20 RANGES OF TOTAL HYDROCARBON CONCENTRATIONS FOR MACRONEKTON Concentration (pg/g, dby weight) Muscle Liver Gill 0.03-7.4 1.1-43.8 0.1-20.0 0.711.6 8.719.6 4.716.1 0.02-4.3 0.6-35.8 0.0-30.6 1.411.3 13.619.8 7.019.4 Species Red Snapper (Lutjanus ocanpeohanus ) Range Mean ± 1 S.D. Vermilion snapper (Bhombop tites aurorubens ) Range Mean ± 1 S.D. TABLE 21 MEANS AND STANDARD DEVIATIONS FOR SELECTED PARAMETERS FROM HEAVY MOLECULAR WEIGHT HYDROCARBON ANALYSES OF MACRONEKTON Species and Organ Lutjanus jRhombopt'ites oampeohanus aurorubens Muscle Liver Muscle Liver ZC 14-18 87.9±25.6 83.4±19.5 91.2±12.5 80.3±22.9 1C 19-24 4.5±10.2 6 6±7 8 5.0±8.3 8.Sill.4 .. ZC 25-32 7.6±19.6 10.0±15.1 3.8±8.9 11.0±13.2 Pristane 13.5±4.8 30.0±24.1 87.7±38.5 81.4±59.1 Phytane Pristane C 1.9±1.5 2 5±1.5 16.3±29.0 10.7±9.9 17 . Phytane C 0.6±0.2 0.9±0.9 1.3±0.8 0.7±0.5 18 CPI 14-20 16.7±9.7 12.7±10.5 22.6±14.3 25.4±35.7 CPI 20-32 1.010.1 2 0±2 2 1.5±0.4 2.914.1 .. n-alkanes. The Cl 9or C23 alkanes had relatively high concentrations in the two with the lowest samples Cl 5 plus Cl 7 concentrations. A wider range of hydrocarbons, as well as higher concentrations of the ClB-C3O n-alkanes, appeared to be present in the spring samples rela­ tive to the fall and winter samples, but the differences were not statis­ tically significant (P < 0.05). The liver, gill and gonad samples also had pentadecane, heptadecane and pristane as the major hydrocarbons with non-significant seasonal changes similar to those found in muscle. Phytane was found in 10% of the muscle samples, in more than 50% of the liver low concentrations. samples and in all of the gonad samples, generally at Small, generally unquantifiable, unresolved complexes were detected in many of the chromatograms. Aromatic compounds were rarely detected and, when found, were generally at the limits of detection (0.005 yg/g). The high-molecular-weight hydrocarbon analysis of macroepifauna and macronekton samples from the STOCS indicated little, if any, petroleum contamination of the study area. No significant spatial trends and few seasonal trends were present in the data, suggesting relative stability in the hydrocarbon pools of the organisms studied. Of the species studied, the brown shrimp, Penaeus aztecus appears to be the best indicator organism for monitoring purposes. Trace Metals Ten trace elements were analyzed in benthic biota including cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), nickel (Ni), lead (Pb), vanadium (V), zinc (Zn), aluminum (Al), and calcium (Ca). Nickel and V were selected because they are present in large concentrations in some oil and tars. Cadmium and Pb, two very toxic metals, are frequently observed to be above natural levels near industrial centers. Copper and Zn are essential trace metals which can reach toxic levels a result of as man’s activities. Iron is also an essential trace element in biological systems (Dulka and Risby, 1976; Brooks, 1977). Iron and Al, because of their abundance in the environment, are important in making geochemical comparisons among trace elements (Trefrey and Presley, 1976b), Finally, Ca is important in identifying potentially severe matrix interferences in our analytical procedures. Table 22 summarizes trace element data for the four selected species of demersal fish in terms of transect sampled. The levels of several trace metals (i.e Cd, Cr. Ni, Pb, V) in fish muscle were at or below the . detection limits of our analytical procedures. For these metals it was obviously not possible to distinguish any spatial or temporal trends. Still, even for elements present in detectable amounts, none of the spe­ cies exhibited any significant geographical patterns in muscle tissue trace element levels. Traohwms lathaml was the only species to show any significant seasonal trends in trace metal concentrations. Aluminum levels in demersal fish exhibited the same seasonal pattern as did zooplankton. Aluminum and Fe in Tvackurus muscle were strongly 2 = correlated (r.41). Also Tvaohurus was the only demersal fish species collected predominantly at nearshore stations. Almost 90% of the samples came from Stations 1 and 2. These facts suggest that the temporal trend in Al levels was a reflection of the more variable nearshore environment which is characterized by sizable seasonal fluctuations in the amount of suspended aluminosilicate particulate matter. The other three species of fish had generally similar concentrations of Al (Table 22), but no seasonal from trends were observed. These species were collected predominantly 950) 850) 600) 850) Ca 700 800 700 500 600 1100 (900-1300) 700 (400-1200) 1900 (700-4500) 700 (400-1400) 750 (550-1000) 1300(750-2000) 1000 (300-2500) 600 (300-1100) 1800 (750-3500) 1200 (750-1600) 800 (550-1200) (400-(350-(300-(350­ 19 Al mean) 25 (19-30) 30 (24-32) 20 (15-25) 30 (16-45) 30 (25-40) 25 (12-55) 30 (15-40) 22 (16-30) 20 (14-30) 13 (10-20) 25 (10-50) 18 (15-25) 17 (14-30) 23 (20-25) 17 (12-30) STUDY around Zn 24 STOCS 13 (11-16) 10 (6.0-12) 14 (11-17) 8.5 (1.0-17) 10 (6.0-14) 13 (6.0-25) 24 (12-35) 10 (2.0-16) 10 (2.0-17) 13 (10-18) 24 (15-40) 14 (10-20) 12(11-16) 12 (6.0-15) 19 (13-25) observed THE <0.10 <0.10 <0.20 <0.15 <0.30 <0-40 <0.10 <0.10 <0.10 <0.10 <0.10 <0.15 <0.10 <0.15 <0.10 <0.10 FROM Interval V FISH /' <0.04 <0.03 <0.08 <0.05 <0.04 <0.05 <0.06 <0.06 <0.05 <0.05 <0.06 <0.10 <0.07 <0.05 <0.04 <0.09 confidence Pb ¦- N1 <0.07 <0.09 <0.10 <0.08 <0.08 <0.08 <0,08 <0.10 <0.07 <0.09 <0.08 <0.10 <0.08 <0.10 <0.08 <0.09 DEMERSAL (95Z weight Fe 9.5 OF 4.5 (2.0-6,0) 3.5 (2.0-5.0) 5.5 (4.0-6.0) 4.0 (I.0-7.0) 3.0 (1.0-5.0) 5.0 (2.0-8.0) 15 (8.0-20) 4.0 (2.0-7.0) 3.0 (2.0-4.0) 4.5 (4.0-5.0) 15(7.0-25) 4.0 (1.8-6.0) 5.5 (4.0-6.0) 4.0 (3.0-6.0) 15 (6.0-25) 22 dry MUSCLE 9) TABLE ppm -3.0) -3.5) Cu 2.4 11. 2.3 2.5 IN in 1.3 (0.70-3.0) 0.95 (0.50-1.6) 1.0(0.70-1.3) 1.4 (0.70-1. 0.90 (0.60-2.0) (0.70-1.7) 1.0 (0.60-1.6) 1.3 (0.50-3.5) 0.90 (0.60-1.1) l.l (0.60-2.0) 0.80 (0.50-1.6) 1.1(0.60-1.5) 2.2 (0.50-3.0) (1.7 (1.7 ELEMENTS Concentration Cr ’-¦ <0.05 <0.05 <0.05 <0.03 <0.04 <0.05 <0.05 <0.05 <0.04 <0.04 <0.05 <0.10 <0.07 <0.07 <0.05 <0.07 TRACE 25) 30) 09) OF Cd <0.05 <0.02 <0.06 <0.04 <0.03 <0.03 <0.05 <0.03 <0.02 <0.06 <0.05 <0.02 <0.05 0.10 (0.01-0, 0.12 (0.01-0. 0.04 (0.01-0. of CONCENTRATIONS Number Samples 7 72 8 798 579 4 238 11 9' 12 AVERAGE Species pomoideaaquilonaria atrobianohua Stenotomua capvinua Traohurua latha/ni Priatipomoidea aquilonaria atrobranahua Stenotomua oaprinua Traohurua lathami Priatipomoidea aquilonaria atrobranahua Stenotomua oaprinua Traohurua lathami Priatipomoidea aquilonaria atrobranohue Stenotomua oaprinua Traohurua lathami Prieti Serranua Serranua Serranua Serranua I 11 IV III Transect offshore stations (i.e. 80% of the samples from Station 3) which are characterized by lower concentrations of organic-rich suspended matter. Trace element data for penaeid shrimp muscle are summarized in Table 23 in terms of station/transect sampled. No significant spatial trends in the data were detected for either species. Penaeus setiferns was only collected from the inshore stations on each transect. Penaeus aztecus , however, was consistently collected from 10 of the 12 stations sampled during this three-year study. Flesh trace element concentrations were not different between the significantly two species {i.e. paired t statistic, < p 0.05). No strong correlations were observed between these data and corresponding sediment trace metal or potential prey organism variables. Aluminum and Fe levels in P. aztecus muscle were strongly correlated 22 == (r 0.72) and both metals exhibited significant correlations (r0.36) with certain,sediment texture parameters. These results suggest that shrimp were assimilating sediment derived A 1 and Fe into their muscle tissue. Zinc levels in P. aztecus did exhibit a significant seasonal effect with a fall maximum. The reason for this relationship is not clear. The trend was not related to differences in the size (age) of shrimp analyzed seasons. The seasonal fluctuations could have been a result of among environmental changes which reflected physiological changes in the 2 < were observed between shrimp. Although no strong correlations (r 0.20) Zn levels and corresponding temperature, salinity or dissolved oxygen conditions at the sampling sites, these parameters were strongly correlated 2 > of (r .32) with Zn concentrations in the hepatopancreas the same shrimp. One of the most striking aspects of this organismal trace element data set This situation is the general lack of any significant spatial trends. may a result of small number of data cases for in part be the generally 700 400 Ca 1200 — 2500 1100 1400 1000 950 (750-1100) 1100 (750-1900) 1500 (450-2500 950 (800-1100) 1100 (850-1500) 900) 2000 (450-3500) (550­mean) 36 13 206018 — A1 STUDY 20 (17-25) 20 (8.0-30) 25 (15-35) 24 (14-34) 20 (17-25) 22 (16-25) 45 (13-90) 24 (18-30) around 30 Zn STOCS observed 45 (20-60) 50 (45-60) 50 (40-55) 50 (40-65) 55 (50-65) 60 (50-70) 50 (40-60) 60 (55-65) 60 (50-70) 50 (40-55) 55 (45-70) 50 (45-60) 50 (45-60) THE V <0.07 <0,05 <0.20 — 0.30 <0.05 <0.10 <0.06 <0.10 0.12 <0.10 <0.05 <0.40 <0,20 Interval FROM rb <0.05 <0.10 <0.07 — <0.15 <0.10 <0.10 <0.05 <0.10 0.08 <0.03 <0.10 <0.15 <0.06 confidence SHRIMP N1 — 0.10 <0.10 <0.10 <0.10 <0.15 <0.10 <0.10 <0.10 <0.08 <0.08 <0.10 <0.30 <0.30 (951! PENAEID weight Fe 3.0 — 2.0 1.0 4.0 dry 3.5 (2.0-5.0) 4.5 (1.0-10) 3.5 (3.0-4.0) 2.5 (0.50-5.0) 6.5 (4.0-12) 4.5 (3.0-6.0) 2.5 (2.0-3.0) 2.0 (1.0-3.0) 13 (3.0-30) OF ppm 23 17 in Cu FLESH 25 (20-30) 21 (19-22) 25 (20-35) 25 (20-30) 24 (19-30) 24 (19-30) 25 (20-30) 25 (25-30) 25 (18-35) 24 (18-35) 24 (20-28) 24 (18-30) 25 (20-30) — Cr TABLE IN Concentration <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.10 <0.10 ELEMENTS Cd 0.13 0.05 0.08 0.05 0.11 0.07 0.10 0.01 0.18 (0.10-0.20) (0.01-0,10) (0.01-0.20) 0.15 (0.13-0.17) 0.08 (0.02-0.12) (0.01-0.12) (0.02-0.25) (0.01-0.11) (0.01-0.25) 0.18 (0.04-0,35) 0.06 (0.01-0.16) 0.08 (0.01-0.13) (0.11-0.25) TRACE of 86 5441 25 4 33 7 Samples OF Number 6 5 autocue aetiferue autocue aatecua autocue aetiferue aatecua aatecua aatecua aatecua aatecua aetiferue aatecua aatecua Species CONCENTRATIONS ' Penaeua Penaeua Penaeua Penaeua Penaeua Penaeua Penaeua Penaeua Penaeua Penaeua Penaeua Penaeua Penaeua Penaeua 2123I 22311 Station AVERAGE 3 I II 111 IV Transect species which made the detection of actual differences difficult. many This absence of geographical trends, however, could be the result of at least two other factors. First, all of the species discussed here are quite mobile. Although the extent of their movements is generally not well documented, it certainly could be significant. This mobility would tend to integrate trace metal exposures at many sites and dampen any differences between them. Second, geographical trends in trace metal levels within the STOCS resulting from man’s activities are probably minimal. Any significant input of trace metals into the STOCS area is most likely to be from diffuse (atmospheric) Due the rela­ sources. to tively small amount of industrialization in the adjacent coastal areas, similar for this atmospheric input is probably quite low and generally the STOCS all parts of region. It is worth noting that all of the significant seasonal trends observed for demersal fauna appeared to be linked to the more changeable nearshore environment. Only species which were collected consistently at nearshore stations exhibited any significant seasonality in trace metal levels. Species collected only at offshore stations showed no seasonal trends. This observation suggests that in future monitoring, any it should be easier to detect changes in the levels of bioavailable trace elements at offshore stations than at nearshore ones. SOUTH TEXAS OUTER ECOSYSTEM CHARACTERISTICS R. W, Flint N. N. Rabalais University of Texas Marine Science Institute, Fort Aransas Texas , General Trends The of the south Texas con­ three-year multidisciplinary study outer tinental shelf resulted in the development of an extensive data base depicting the physical, chemical and biological characteristics of an extremely Important marine subtidal area in terms of natural resources. The Texas shelf can be described as a very dynamic system driven by a complex aggregation of meteorological and oceanographical events, includ­ ing diverse wind and current structures. Superimposed upon these phenomena are influences to the system both from local rivers and estuaries as well as distant factors such as the Mississippi River and deep ocean waters of the Gulf basin. a ocean environment in terms of The ecosystem represents typical nutrient concentrations and associated annual dynamics. The Texas shelf is relatively pristine in respect to the pollutants monitored during this study, such as hydrocarbons and trace metal concentrations, with the majority of hydrocarbon observations related to natural phenomena, during the study period. biomasses with The shelf supports relatively high phytoplantkon extremely high annual production especially in the inner-shelf waters. characteristics are Many of the phytoplankton strongly related to salinity and incident solar radiation as well as possible nutrient regeneration. Most of the marine biota observed in this study show strong geographical trends, usually related to water depth or distance from shore, as illus­ trated in Figure 52. The plankton are most abundant along the inner- shelf. Their numbers are predictably large in the spring, correlated with riverine inputs and nutrient maxima. The inner-shelf maxima for phytoplankton were also reflected in zoo- plankton (Figure 52). Peaks in zooplankton biomass were observed at shallow sites with decreases occurring in an offshore direction. Both infaunal and epifaunal (as represented by Penaeus azteous densities) organisms were more numerous along the inner shelf where general produc­ tivity was greater in response to increased food supplies. An additional factor potentially controlling the infaunal and epifaunal organisms appeared to be the coarser-grained sediments at the shallow sites. These pro- may vide a more suitable habitat than the finer silts and clays of the outer shelf environment. The larger and more mobile fauna, such as the demersal fish,showed less spatial patterning in their distributions on the shelf. The ichthyo­ plankton, however, which werestrongly correlated with zooplankton, were far more abundant on the Texas inner shelf. It appears reasonable to con- that the shallower areas of the south Texas shelf a clude are biologically more critical part of this marine ecosystem. The changes in fauna observed suggest that the inner-shelf region is a much more dynamic area than the waters near the shelf break. In addi­ tion, much of the riverine input to the south Texas shelf enters through have well-developed estuaries. These estuaries undoubtedly an important impact on the shelf which may be manifested in some of the gradients illustrated in Figure 52. The isothermal conditions from the surface waters to the presence of Penaeus and density, infaunal benthic biomass, zooplankton a_, chlorophyll of Relationships 52. Figure continental Texascouter south plot. the each for for (m) depth indicated are water (r) with densitycoefficients shrimp) (brown Correlation azteous shelf. sea-floor during much of the year allows for considerable interaction between two dynamic communities in the inner-shelf region of the Texas coast: 1) a benthic community consisting of those organisms living in or on the sediment or near the sediment-water interface; and 2) a pelagic community consisting of those organisms drifting, floating, or swimming in the overlying waters. Because of their interactions, the boundaries of these two communities are not clear. Many nekton organisms, for example, deposit eggs which become part of the benthic community while the larvae and adults are members of the pelagic community. Conversely, numerous benthic species produce eggs which float in the water column, hatch into planktonic to the larvae and become dispersed by currents before settling permanently bottom. In addition to the above interactions, demersal fishes swim into the pelagic zone to feed on plankton while the benthos depends upon the continual "rain" of materials (e.g. algae, fecal pellets) from the over­ lying waters for nourishment. Nutrient Regeneration Evidence from the three-year study indicates that the Texas shelf waters, especially inner-shelf waters, are extremely productive in plant biomass. Further evidence for this high production comes from the fact that several important commercial fisheries are supported in these same waters. Rowe et at. (1975) recently contended that nutrient regeneration in sediments is the major factor responsible for the relatively high rate of primary carbon fixation in continental shelf waters. They indicated ammo- that the lack of bottom sediment contributions of nutrients such as nia would cause the loss of an important "feedback" to the system, which would leave the pelagic primary producers dependent solely on water column sources of nutrients. They speculated that if this were the case, shelf break. The conclusions stated above (Rowe et at, 1975) were based primarily , on two observations. First, they observed gradients of decreasing ammonium (NH*) concentrations between the benthos and overlying water column. Secondly, they estimated potential releases of ammonia by the sediments from measurements of respiration, assuming the oxidation of organic matter, including infaunal metabolism, would result in ammonia release. to More recently Carpenter and McCarthy (1978) attempted shed doubt on the hypothesis of Rowe et at, (1975) by contending that on the conti­ nental shelf the sediments play a minor role in cycling nitrogenous nutri­ ents for primary producers. Part of the basis for their contention was in the water column of a shelf habitat do not have that primary producers enough of their diverted the benthos cause rates of ammonia energy to to regeneration by the sediments as reported by Rowe et at, (1975), because much of the shelf. their energy is utilized by zooplankton and nekton on Carpenter and McCarthy (1978) felt that for regeneration rates as reported the sediments would have to receive by Rowe et at, (1975) to be occurring, supplemental supplies of allochthonous organic materials. As will be illustrated later in this chapter, data collected on the Texas shelf indi­ cate that the majority of phytoplankton biomass produced on the STOCS inner-shelf waters does not go as energy to pelagic components of the system but rather is diverted directly to the benthos. Data collected during several special cruises in the STOCS study, which were intended to trace the nepheloid layer dynamics on the Texas shelf, lend support to the original hypothesis put forth by Rowe and his colleagues. Figure 53 illustrates diel ammonium (NH*) profiles through the during depth with concentrations nitrogen ammonia for profiles hour) (by Temporal 53. Figure 11. Transect 4, Station near location sampling a at indicated periods sampling the water column at a station of approximately 33 m water depth on the Texas shelf during four periods in 1978. Almost every profile illustrates a gradient in ammonia through the water column with increases in concentra­ tion near the mud-water interface. These data collected during both were conditions of water column stratification and non-stratification and showed similar trends during both. In addition, results presented in Chapter 3 (Figure 20) indicate that the peaks in bottom water nitrogen were often associated with chlorophyll peaks. In conjunction with these peaks, photosynthesis was shown to be occurring, suggesting that the nutri ent concentrations are being utilized by primary producers. Given the observations by Rowe et al, (1975) plus the experiences cited above for Texas shelf waters, there appears to be sufficient evidence to support the idea of sediment nutrient regeneration being at least par­ tially responsible for higher rates of primary production in shelf waters. Under circumstances like these the bottom serve as a nutrient reser­ may voir and may dampen the effects of surface productivity cycles. Further­ more, the occurrence of this phenomena on the south Texas shelf emphasizes of several other ecosystem mechanisms that should be the importance briefly mentioned. As stated above, the sediments of the STOCS act as a ecosystem may reservoir for nitrogenous compounds such as ammonia that are potentially usable for primary producers. Besides the apparent flux of ammonia out of the sediments, generated by gradients between the sediments and over­ lying water, there is another possible mechanism for nutrient release on the Texas shelf which is directly related to the consistent occurrence of the nepheloid layer. As suggested in Chapter 3, the nepheloid layer The nature is the result of sediment resuspension. silty-mud of Texas shelf sediments help to perpetuate the presence of a nepheloid layer in these bottom waters. The benthic fauna, as well as macroepifaunal species which may disturb and otherwise bioturbate the bottom sediments, poten­ tially serve as other influencing factors in the maintenance of this nepheloid layer with its associated nutrients, plant biomass and detritus The biological dynamics of the fauna in and on the sediments potentially provide aeration to the interstitial water and sediments as well as dif­ ferent degrees of substrate coherence and stability, dependent upon the type of biological function that occurs. The recycling and release of nutrients as well as sediment detritus to the water column depend largely on the ease with which the muddy sea- floor can be resuspended. Bioturbation and current turbulence control this process (Rhoads et at., 1974). Knowledge of the overall extent of biogenic activity is a key to partially predicting the consistency of nepheloid layer occurrence over various parts of the shelf. Furthermore, it is likely that the bioturbation activities of the benthic fauna play a role not only in the dynamics of the nepheloid layer but also in the the mud- general mechanisms responsible for nutrient regeneration across water interface. According to the evidence cited above and by Rowe et at of the Texas shelf could (1975), these nutrient regeneration dynamics serve as a major force and responsible for some of driving the ecosystem this shelf. the extremely productive fisheries supported by Trophic Coupling For many years immense amounts of information have been accumulating on abundance and the distribution of ben­ primary production, zooplankton thic organisms in Important fishing areas. Despite these data bases it is very difficult to describe quantitatively the links between primary A these to production and fish yields. few plausible attempts quantify and links have been provided by Steele (1974) for the North Sea ecosystem by Mills and Fournier (in press) for the Scotian Shelf system. Even with­ out complete data bases, the comparison of regions like the North Sea, the Scotian shelf, and for example, the northwestern Gulf of Mexico shelf, should offer insight into the general structure of marine ecosystems and pinpoint deficiencies in our understanding of them. Of most concern here is the need to take a hard look at the hypothesis that, despite geograph­ ical differences, most coastal ecosystems with productive fisheries have similarly constructed food webs (Dickie, 1972; Mills, 1975). an The importance of understanding the functioning of ecosystem, especially with respect to an important fishery, cannot be overemphasized. For example, to demonstrate the effect on an ecosystem from perturbation such as an oil spill and to relate that directly to an impact on man, the effect to a natural resource such as a refinery must be cited. This effect on fishery productivity as reflected by commercial catch statistics is extremely risky at best. There are several shortcomings in fishery catch statistics. do not They represent precise reporting because they fail to take into account effort and technological advances the changing of fisheries. They also are generally not available for the localized areas in which the perturbation may be intense. Based on these shortcomings and the desire to better understand the components of an important resource to the Texas shelf, we decided to use both the STOCS data base as well as bibliographical information to derive a conceptual model of the trophic relations involved in the shrimp fishery on the shelf. Through correlation research, relationships were sought between different components of the STOCS data base that intuitively made biological sense. The results of this search were the development of a conceptual model, based on correlation coefficients, that suggested rela­ tionships between the water column, benthos and shrimp that could serve as the basis upon which to create a food web hypothesis. 54. These relationships are depicted in Figure Only significant correlation coefficients (P < 0.05) are illustrated. The model emphasizes several patterns. There is a relationship between the water column fauna, in this case zooplankton, and the sediment detrital pool, illustrated by the correlations between zooplankton nickel body burdens and sediment nickel concentrations as well as several zooplankton hydrocarbon body burden variables and hydrocarbons observed in the sediment. The hypothe­ sis that could be derived from these results is that zooplankton fecal pellets serve as a major input to marine sediment detrital pools. This has been verified by numerous studies (Steele, 1974) . In addition to zooplankton inputs to the benthos, the data indicate that primary producer biomass, as represented by bottom water chlorophyll concentrations, is related to densities of benthic infauna and bacteria, the potentially through the detrital pool (Figure 54). Furthermore, relationships depicted by the model suggest the suspended relation between sediment hydrocarbon concentrations and bacteria with the former serving as a potential food source. 54 for the The interrelationships that are suggested in Figure various faunal size categories living within the sediments (bacteria, meiofauna, and macrofauna) are relatively strong and provide further insight into the functioning of the Texas shelf benthos. The constant ratio of benthic animals to bacteria, and not organic carbon, indicates that benthic animals are more related to bacteria than to organic carbon. that benthic animals utilize bacteria as a This relationship suggests food source and not organic carbon. Bacteria are considered a major food STOCS the between found correlations 0.01) < (P significant of representation Schematic 54. Figure also are (n) cases of number and (r) coefficients correlation The indicated. variables shown. item for a wide variety of meiofauna (Coull, 1973) and macrofauna (Zobell and Feltham, 1938; Newell, 1965; Chua and Brinkhurst, 1973). There are some indications that the meiofauna may contribute more to the matter and energy cycles of the sea than was envisaged by earlier investigators (Perkins, 1958; Mclntyre, 1969). Recent caging experiments (Bell and Coull, 1978; Rubright, 1978; Buzas, 1978) have shown that meio­ faunal populations, particularly the Nematoda, the Foraminiferida and the Polychaeta, are substantially reduced by predation and, therefore, prob- Buzas ably represent an important food source. (1978) performed predator exclusion experiments in which foraminiferal biomass inside meiofaunal 2 cages were 3 to 12 g/mhigher than outside the cages. This suggested foraminiferal densities were significantly reduced by predation. Another study by Bell and Coull (1978) indicated that Falaemonetes (grass shrimp) predation/disturbance significantly lowered total meiofaunal densities and that the shrimp randomly fed on the available nematodes in proportion to their abundance. Macrofauna acting as surface deposit feeders can shift to subsurface deposit feeding when high quality sedimentated food following a spring phytoplankton bloom diminishes. Others are exclusively subsurface deposit feeders. Much meiofaunal predation may be incidental to non-selective subsurface deposit feeding. In the sediment, the organic food is more refractive and the energy source available to macro-and meiofauna is via bacteria and organic fractions which can be digested (Gerlach, 1971). Gerlach (1978) further stated that although the estimates of meio­ faunal contribution to the organic content of sediment utilized by sub­ surface deposit feeders was considered low, the bacterial biomass was not much higher than meiofaunal biomass. He further stated that meio­ very fauna must be considered an important food source if the concept of non-selective feeding is valid. Similar complex feeding modes are found within the meiofauna. With increased study on the life histories of meiofauna, as has been the case with the macrofauna, the classical consensus that meiofauna are detrital feeders or indiscriminant feeders on benthic diatoms and bacteria (Wieser, 1960) has been replaced with the idea that they show as varied a feeding mode and diet as exists in the sediments (Coull, 1973). Some meiofauna are active predators. Many feed on bacteria and protozoa in competition with macro;:auna, and others assimilate dissolved organic matter directly. The primary function of meiobenthos in trophic relationships has nutrients at a traditionally been the assistance of recycling low trophic level (Mclntyre, 1969). However, added importance is now being attributed to meiofauna in the enhancement of microbiota environment (growth) on detritus. Growth of an associated microbiota is enhanced when the detri­ tal feeder mechanically breaks down the particle and increases the surface to volume size, thus furthering the microbial growth and decomposition (Coull, 1973). There is little doubt that particulate organic detritus the meiofauna. Gerlach stated is consumed in great quantities by (1978) that in situ sediment bacterial production is far below potential rates and somewhat stationary. Furthermore, he found that faunal activities may be beneficial for bacterial growth in marine sediments and may stimu­ late the rate of detritus decomposition. This statement applies to micro­ ns well as meiofauna, which would place both categories back into the same complex food web, Meiofauna may be more efficient, however, in utilizing organic substrates than macrofauna (Gerlach, 1978). Gerlach (1978) reported more specific relationships between meiofauna and sediment bacteria. In microcosm experiments, the breakdown of 1Re­ labelled Zostera detritus was greater when meiofauna was than when present there were only polychaetes. Nematodes may share with protozoa a major role in benthic nutrient regeneration and prevent bacteria from reaching self-limiting numbers. More specific interactions between meiofauna and bacteria were also reported by Gerlach (1978) in which the cuticle of cer­ tain nematodes were covered with a sheet of densely packed bacteria which they fed on and "gardened" by providing favorable environmental conditions; for example, by migrating up and down between aerobic and sulfide layers of the sediments. Other simple associations such as "mucus traps" on nematodes to which organic particles adhere resulting in a subsequent bacterial growth may be more widely distributed in marine sediments than is now known. a ties the Finally, Figure 54 depicts relationship that potentially density of shrimp on the Texas shelf to the functioning of other major components of the ecosystem. There are strong.correlations shown for shrimp body burdens of nickel and total hydrocarbons with sediment nickel concentrations and a hydrocarbon variable, suggesting that shrimp may derive their nutrition from the benthos. More important, however, are the relationships that are portrayed for nickel concentrations throughout the model depicted in Figure 54 (zooplankton -.sediment -.shrimp) These . for correlations make it possible to propose a trophic coupling hypothesis shrimp which includes both pelagic and benthic components. It is quite clear than in inner-shelf waters, where mixing occurs, resulting in a relatively homogeneous water column, the discrimination between pelagic and benthic components is very obscure and the potential for trophic coupling between the two becomes very important. The nearshore subtidal region of the Texas coast with its many interacting communities is the site of several major fisheries including detailed in Figure 54, we feel it is imperative to examine some of the interactions of this region and relate them to a of immense trophic fishery economic importance, in order to delineate the deficiencies in our under­ standing. Outside the bays and estuaries, the shrimp fishery extends to imately 80 m depth on the shelf, with maximums in yield obtained well inside this range. Annual shrimp landing reports (NOAA/NMFS Gulf Coast Shrimp Data, Annual Summaries) indicate that for the reporting area (Statistical Area #2O) similar to STOCS stations monitored during 1975­ 6 1977 (Figure 55), an annual average of 5.7 x 10 kg of shrimp were landed for the years 1975-1976. This represented a mean value of 18 million dollars for that period to the commercial fishery. For purposes of developing a conceptual model, a single station centeredin themiddle of the fishery reporting area described above, which was monitored on almost a monthly basis for the period 1976-1977 will be emphasized. This station. Stationl/II (reference station. Figure 55) was located off Aransas Pass Inlet in approximately 22 m water depth. for Texas inner-shelf waters as characterized by Primary production the above station somewhat bimodal on an annual basis with peaks in was the spring and fall (Chapter 3, Figure 17), Annual estimates of produc­ tion based upon chlorophyll a. measures converted to carbon equivalents according to methods of Ryther and Yentsch (1957) indicated that these 2 of 103 waters produced a mean approximately g C/m/yr (Figure 56). Macrozooplankton biomass on the Texas shelf averaged approximately 2 3.566 g/m wet weight over the sampling interval. Assuming a turn-over of was ratio of 7 (Steele, 1974), annual production the macrozooplankton 2 estimated to be 25 g/m /yr. Since the water column was usually fairly Figure 55. Location of the reference station focused upon in the NOAA statistical reporting area (rectangular boxed area), for the development of a trophic model for shrimp. indicated transfers Material fishery. shrimp brown the for model /yr. 2 trophic Conceptual 56, Figure gC/m in also are homogeneous and the zooplankton tows often did not reach the bottom, plus sampling bias from net clogging, it is likely that the number for 2 production estimate should be doubled to 50 g/m /yr for purposes of this model. 6% Assuming approximately a conversion between wet weight and carbon content of metazoans (Rowe, personal communication) the carbon 2 equivalent of zooplankton production was estimated to be 3 g C/m/yr (Figure 56). Information on the neuston component of the planktonic community 2 indicated that an additional 0.21 g C/m /yr could be assumed for the macroplankton production from these surface animals. Standing crop of 2 to microplankton was calculated be 465 mg/m wet weight. Annual produc­ tion was estimated as 10 times the standing crop because of larger expected turnover ratios for the microplankton. With the conversion to carbon content mentioned above this resulted in approximately 0,9 g C/m2 /yr Therefore, the total production estimate for the zooplankton component 2 of the food web on the Texas inner shelf is approximately 4.1 g C/m /yr (Figure 56). If we assume a minimum transfer efficiency of 20% (very conservative) between primary producers and the zooplankton, then 20.5 g C/m2/yr (Fig­ ure 56) would be required to support the zooplankton. This transfer of 2 carbon results in approximately 82 g C/m /yr of primary production remaining. Mills and Fournier (in press) indicated that, contrasted with the North Sea ecosystem (Steele, 1974), for the coastal ecosystem was diverted to on the Scotian Shelf the majority of primary production the demersal fisheries. This may very well be the case for the Gulf coastal ecosystem also. The bottom waters appear to support greater amounts of primary producers than the surface or mid depths during the The amount of pelagic fisheries biomass that is directly supported by primary producers on the Texas inner shelf is unknown. From the amount of zooplankton production observed, however, one would have to assume that the pelagic fisheries is small. Therefore, the Texas inner-shelf ecosys­ tem is probably characterized as a system where the majority of primary production is input directly to the bottom waters and benthos. Information from Steele (1974) indicated that 30% of the primary pro­ duction is transported to the benthos in the North Sea ecosystem. From the above facts, plus if we assume there are no other major links to pela­ gic fisheries other than through zooplankton, it would appear that almost 80% of this production reaches the benthos in the Texas coastal waters. This is probably an over-estimation but the real number is certainly greater than the 30% estimated for the North Sea. To further illustrate the input to the bottom, data from several cruises to examine nepheloid layer dynamics, which were detailed in Chapter 3, substantiate the presence of peak chlorophyll layers in these bottom waters. the direct input to the ben- The carbon production at depth plus thos of detritus, both from the nepheloid layer and the upper portions of the water column, presumably can provide a sizable nutritional source for demersalroriented trophic links. Estimates of benthic infaunal biomass in this region of the Texas 2 inner shelf range between 0.5 g/m2 (STOCS study) and 2.5 g/m (Rowe et al, 1974; Table 24). Assuming a turnover ratio of approximately 4,5 (Nichols, 2 1978), an average of 0.29 g C/m/yr are produced by the infaunal benthos (Figure 56). Shrimp fisheries yields (NOAA/NMFS Gulf Coast Shrimp Data, Annual 3 ) 2 Weight (g/m 0.63 0.28 0,46 respective Wet OCEAN the 2 of ) 675 Density (#/m 1,536 1,106 tatlo ATLANTIC 2 Mexico weight of ) 2 Weight (g/m 0.74 4.09 2.42 wet NORTHWESTERN 1 Gulf Wet to -1977. THE 1 MEXICO 1975-density ) 2 FROM Density (*/m 1,373 14,623 7,998 the OF Study, 24 GULF Using Shelf MACROBENTHOS TABLE 12 1630 Depth(m) OF NORTHWESTERN otganisms Continental BIOMASS AND of AND Outer Weight densities 2(g/m) 7.69 2.44 5.07 (1974). Wet Texas (1974). i ABUNDANCE at, South from . Ocean OF et ) 7,390 Rowe the Rowe Density (.#/ 26,060 16,725 et calculated at Atlantic 2 from from COMPARISON m fromweight 30 40 Depth (m) Average Measures Measures Wet values 3 2 used on an annual Summaries). were to estimate the production of shrimp basis for the inner-shelf waters. Utilizing the suggested conversions to obtain the heads-on weight and assuming a turnover ratio of approximately (Caillouet, NMFS, personal communication), the commercial fishery 2 catch represented approximately 0.03 g C/m /yr of shrimp production. According to the hypothesized survival curve presented in Figure 57 this estimate of shrimp production was for approximately 78% of the shelf pop­ ulation in statistical area #2O (Figure 55). Therefore, adding the other 22% of the population, annual production was estimated to be 0.04 g C/m2/yr (Figure 56). 2 Data from the STOCS study indicated that an additional 0.02 g C/m /yr of other demersal species was produced on the inner shelf. The combination of this data with the shrimp production estimates illustrated that approx­ 2 in these bottom imately 0.06 g C/m/yr was produced by the fauna living waters of the Texas shelf. Comparing this trophic level to the infaunal production and assuming a standard 10% transfer efficiency, it would appear that benthic biomass is an insufficient food source to solely support the demersal component of the inner-shelf food web. These figures do not include meiofaunal production, but even if this component were known, there probably would still not be enough biomass to directly support the demersal fisheries. Furthermore, as illustrated in Table 24, there appears to be much less benthic infaunal production in the northwestern Gulf of Mexico contrasted to other continental shelf regions such as the north­ western Atlantic, This is surprising considering the extensive fishery supported on the Gulf continental shelf. The alternative to an infaunal-demersal fishery trophic link is a detrital based trophic web for many of the commercially important species. along range size to according area) (shaded yield fishery shrimp reported the of Plot 57. Figure shrimp brown shelf Texas south the for line) (solid curve survivorship estimated an population. with centrations of chlorophyll in the bottom waters along with a relatively small amount of pelagic secondary production would tend to support this conclusion. If the Texas inner shelf trophically revolves around a detrital food web, one of several questions to ask concerns where the benthos fit into since do this trophic scheme; especially they not appear to have the bio­ mass to alone support the observed production at higher trophic levels. A possible hypothesis for the role of the benthos takes into account the dynamics of the nepheloid layer. Rhoads et al (1974) pointed out that . the concentration of solids in estuaries and coastal waters suspended many is higher in the bottom waters than at the surface, where the especially water column passes over muds that have undergone intensive bioturbation. As stated previously, the recycling of materials, such as detritus, from the sediment, to the bottom waters depends largely on the ease with which the muddy sea floor can be resuspended. Bioturbation by infauna and current scour control this process (Rhoads et al 1974). Primary produc­ ., tivity in turn provides plankters to the bottom waters through surface sedimentation. Both living and dead plankters plus associated microorgan­ isms produce detrital food for demersal consumers including shrimp popula­ tions, Thus, benthic infauna do not necessarily provide all of the direct food sources for an important fishery such as shrimp, but rather sup­ plement the demersal consumer 1 s diet and indirectly provide alternative nutritional sources through their bioturbation activities and the mainte­ nance of a very productive zone in the near-shelf bottom waters. In turn, the extremely high densities of shrimp on the Gulf of Mexico shelf, as indicated by the successful fishery, probably have a direct effect on the smaller benthic infaunal biomasses observed for these waters as contrasted to the Atlantic coastal waters (Table 24). The predation pressure of the shrimp plus their physical feeding activities may serve as influential factors in maintaining infaunal organisms at relatively smaller sizes with possibly higher turnover ratios than even assumed here From the preceding exercise it is obvious that the coastal waters of the Gulf of Mexico are extremely productive and that this production is influenced by many factors. It is suggested that much of this produc­ tion is to diverted directly the benthos and that the major regional fisheries, such as shrimp, receive much of their nutrition from a detri­ tal food web. Determining the mechanisms of this food web and the exact role of such components as the benthos is an extremely important task for future research. It would appear that this ecosystem, and its food webs leading to major commercial fisheries, is certainly different in struc­ ture than, for example, the system described by Steele (1974) for the North Sea. This points to the need for detailed regional studies before generalizations and models to predict effects from such factors as environmental disturbance can be constructed for important fisheries. Environmental Disturbance In the state of Texas, one-third of the population resides in the coastal zone. A total population of 3.5 million was recorded for the state in 1975 with the population projected to increase to 5 million by 1980. Such dynamic growth in Texas and throughout the United States implies parallel expansion in the coastal zone with increased demands for manufacturing, petroleum and natural gas exploration, production, and refining, increased marine transportation, commercial use of natural and recreation and tourism. resources, The pressures imposed by a rapidly increasing population demand coastal waters make up less than one percent of the world T s oceans, yet it is in this fringe that are found the most productive ecosystems in the world. The different water masses influencing the Texas shelf, in particular freshwater discharge, suggest that as salinity decreases from riverine input the particulate matter increases along with possible associated nutrients and primary productivity. The effects of this scheme are felt throughout the south Texas shelf. Thus, the outer con­ tinental shelf system is not just a product of the dynamics of Gulf waters but a reflection of in nearshore coastal waters many processes as well. Our continued multiplicity of demands upon the complex coastal environments make it imperative that their functioning and ecological values be understood. This knowledge is essential for decision makers to properly manage coastal environments while maintaining the best pos­ sible conditions for the continued productive uses of natural resources. Healthy, naturally functioning ecosystems are one of the principal resources in the northwestern Gulf of Mexico that are susceptible to environmental disturbance, such as oil spills. The benefits we from reap include multi-millionboth these systems dollar commercial fisheries, shellfish and finfish, and particularly penaeid shrimp. The health of the general public can be threatened by contaminated foodstuff passing through the fishery markets. A sizable sports fishery also harvests these resources. An important segment of our coastal economy is based on recreation and tourism which in turn are dependent upon the natural resources. Additionally, segments of the shelf ecosystem provide habitats for endangered and threatened species, such as sea turtles. Billions of dollars are contributed to our the northwestern per year economy from Gulf of Mexico as a result of all these fish and wildlife populations. In addition, the Gulf coastal zone must be considered one of the most resources. centers critical nonliving Population naturally develop along the coast and serve as focal points for national and international com­ merce as well as recreation. Wastes of various kinds normally enter Gulf waters by direct discharge from coastal municipalities and industries or streams that serve as transmission media for waters through tributary from larger areas. Included in this waste are raw and partially treated municipal sewage, industrial wastes including petroleum products, and sediment loads from soil erosion. In an era of increased energy demands, the coastal zone is an area which may be affected by oil and gas explor­ ation and production, oil spills, increased marine transportation, and manufacturing and industrialization. A potential exists for increased amounts enter to sources and of pollutants to the system. Impacts these areas from an environmental disturbance may include loss of income from decreased fisheries, tourism and/or recreation, health dangers, and dam­ age to natural resources. The objectives of the three-year study of the south Texas outer con­ tinental shelf were to describe the physical, chemical and biological components of the system and their interactions, against which subsequent changes or impacts could be compared, particularly in light of the effects of outer continental shelf oil and gas development activities. The synthesis and integration of this data was designed to develop an encompassing description of the study area, identifying the temporal and trends with mathematical spatial that best represented the ecosystem along as descriptions for unique relationships that would serve "fingerprints’1 for future comparisons. The study results indicate that a major step has been taken toward reaching this objective. Our analyses have shown the south Texas shelf to have been found between the physical, chemical and biological components studied, and naturally inherent variability has been quantified. Poten­ tial, implicative, or biologically intuitive relationships have been hypoth­ esized which describe some of the forcing dynamics of this system, but these exercises only serve to point out the need for detailed studies before overall generalizations and predictive models can be constructed. Evidence from indicates that the south Texas shelf bottom the study environment is relatively pristine with respect to those chemicals moni­ tored during the study period. There is minimal petroleum pollution of sediments (lack of aromatic hydrocarbons), and these appear to be free of trace metal contamination. the water column is any significant Likewise, with those relatively pristine with respect to the hydrocarbons studied, observations during the study attributed primarily to natural sources such as suspected natural gas seeps along the edge of the shelf. Because of the tremendous quantities of available dilution water from local and Miss­ issippi riverine input, pollution wastes originating in the coastal area to resources have, date, had minimal effects upon either water quality or in the Gulf of Mexico. There is, however, increasing pressure to further develop many of the resources in the Gulf which can threaten energy severely the pristine nature of the waters, especially in terms of hydrocarbons. The ecological effects of oil pollution on the Texas shelf environ­ ment are an important consideration in energy policy decisions directed at this area, primarily because of economic consideration such as the extensive commercial fisheries. of the environmental assessment At present, impact of energy resource development must be made somewhat in ignorance and uncertainty because of large knowledge gaps and conflicting opinions. 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Mclntyre. 1964. quantitative comparisons of offshore meiobenthos and macrobenthos south of Martha’s Vineyard. Limnol. Oceanogr. 9(4):485-493. Wiist, G. 1964. Stratification and circulation in the Antillean-Caribbean basins. Part I. Columbia Univ. Press, N.Y. 201pp. Zobell, C. E., and C. B. Feltham. 1938. Bacteria as food for certain marine invertebrates. J, Mar. Res. 1:312-327. APPENDIX A OVERALL BASELINE RESULTS DISTRIBUTIONAL CHARACTERISTICS OF SELECTED IMPORTANT VARIABLES 1 The purpose of this appendix is to present baseline information for the South Texas Outer Continental Shelf (STOCS) for the period 1975-1977. Presented are the distributional characteristics (i.e standard mean, . deviation, skewness, kurtosis and confidence intervals) for parameters selected from each of the areas of the STOCS integration study study effort. Also presented is information concerning significant temporal and spatial variation for these parameters. The actual numerical results are presented in Table A-10 at the end sections: of this appendix. Preceding Table A-10 are several explanatory 1) a section describing the format and use of Table A-10; 2) an overview of the sampling scheme of the STOCS study; 3) a methodology section describ ing the ’selectLion of variables and the statistical methods used; 4) a section discussing the comparison of the present baseline results to future monitoring results; 5) a section discussing the number of samples needed in future monitoring efforts; and 6) an index of study areas for Table A-10. No attempt has been made in this appendix to discuss the scientific meaning or implications of the various numerical results. this Such discussion has already been presented in the main text of volume and in Volume 111. It is hoped that the present appendix will allow future workers to efficiently locate desired baseline results and these results to values from future monitoring efforts. to quickly compare Format and Use of Table A-10 Table A-10 has been organized to present several different types of A results and the format is somewhat complicated. set of hypothetical *Text of appendix by R. Godbout, STOCS Data Manager results is presented in Table A-l which will serve to illustrate the gen­ eral format of Table A-10. These column titles in the table refer to the distribution statistics presented for each variable; STD DEV-standard deviation; SKEW-skewness; KURT-kurtosis; 95% EMPIR CI-95% empirical con­ fidence interval; and N-the number of data cases involved. The actual methods used to calculate the different distribution statistics are spelled out in the methodology section of this appendix. In Table A-l, "High-Molecular-Weight Hydrocarbons in Epifauna", indicates the study area for the variables which follow. In parentheses after the study area title are the years for which data are being consid­ 1976 to Note that the variables which follow ered, 1977 in this example. a are relevant to specific species (Rhomboplites aurorubens ) and a spe­ cific tissue (liver). The first for this species-tissue combination is "Total Hydrocarbons". This variable is the of the normal alkanes sum involving from 14 to 32 carbon atoms (n-Cn* to n-Ca2) and the units for this variable are micrograms per gram. There was a total of 50 cases considered for the Total Hydrocarbon variable and the overall mean was 13.60; the overall standard deviation, 9.78; etc. Note that "Total Hydrocarbons" is then broken down by station and then by year. For example, the 20 data cases for Station 1 had a mean of 13.04 and a standard deviation of 8.79; while the 15 data cases for 1976 had a mean of 10.68 and a standard deviation of 9.63. The fact that breakdowns by station and by year are presented for differences "Total Hydrocarbons" signifies that valid significant (beyond the 0.05 level of significance) were found the three stations and among also between the two years. In general, a series of analyses of variance The actual analyses performed and the rationale for these analyses are presented in the methodology section of this appendix. 1 N 50 20 20 10 1535 40 42 35.80 32.91 35.80 \o 29.78 28.76 36.00 7.03 00 Cl 171.60 EMPIR CN - 1 -­ 95% 0.57 0.57 2.98 6.29 5.43 0.57 1.85 7.03 17.27 FORMAT KURT 0.08 0.01 -0.05 0.18 0.07 0.08 -1.34 2.02 A-10 TABLE SKEW 0.84 0.73 0.74 0.92 0.80 0.85 0.79 1.65 A-l ILLUSTRATING DEV 9.78 8.79 9.30 10.64 9.63 9.43 9.92 59.10 TABLE STD RESULTS MEAN 13.60 13.04 15.96 11.26 10.68 14.91 81.41 10.67 7.03 HYPOTHETICAL HYDROCARBONS ) aurorubens 32123 7 n-C i HYDROCARBONS to Station Station Station 1976 1977 Winter (micrograms/gm) PRISTANE/PHYTANE PRISTANE/n-C TOTAL (n-Cm Liver HIGH-MOLECULAR-WEIGHT EPIFAUNA (1976-1977) Rhomboplites A-5 54 1 N 3514 46 54 Cl 8.22 36.00 28.72 16.92 6.77 10.32 11.92 1.85 1.50 m — EMPIR — 95% 3.85 5.94 6.92 1.85 4.93 6.91 7.12 1,85 0.17 KURT 1.42 2.12 1.92 1.62 2.60 2.11 -1.60 SKEW -0.49 2.91 3.41 1.56 1.72 1.82 1.84 0.46 0 H Z O O DEV i-1 2.98 7.63 6.99 9.67 9.56 0.52 10.42 10.80 > s 20 1 « 3 0* « £ 15 10 1 i 5 i1 //, /I s // s 2 -1 0 1 2 3 4 5 8 7 8 91011 12 13 Pristan* / Phytan* in sodimonts Figure A-2. Example comparison of empirical and normal curve confidence intervals. population of values. While empirical confidence intervals are generally applicable they should be interpreted with some caution. The empirical confidence inter­ val is most greatly influenced by the extreme values in a distribution. Extreme values are most subject to sampling and therefore the error, empirical confidence interval can be greatly influenced by sampling error. In contrast, the normal distribution confidence interval will be less of a function of sampling error since it is not so dependent upon the extreme and most errorful values in a distribution. All of these considerations about confidence intervals suggest the following recommendations for a user of Table A-10. Inspect the skewness values for If neither are differ and kurtosis a parameter. significantly ent from 0, then assume that the distribution is normal. The normal dis­ tribution confidence interval should then be calculated and used to best describe that variable. If either skewness or kurtosis is significantly different from 0, then assume that the distribution is not normal. In the empirical confidence interval should best describe that this case, variable. Analysis of Spatial and Temporal Effects to and Each variable in Table A-10 was analyzed with regard temporal more spatial variation. The analysis procedures employed were complicated of than one might anticipate. The complexity arose for two types reasons. of First, from a statistical point of view, several aspects of the design evolved the STOCS study were quite haphazard. The purpose of the study from from year to year with corresponding design changes occurring year taken for each collec­ to year. Replicate samples (a series of samples tion period and site combination) were taken inconsistently, thereby data further aggravated our problems. Second, time constraints ruled out the use of different analysis approaches for different variables. It was necessary to arrive at an automated system which could uniformly be applied to all variables. Such a uniform approach further sacrificed analytic simplicity. The temporal effects analyzed were collection period and year while the spatial effects analyzed were station and transect. For many variables replicate samples (different samples taken at the same time, collection period and year) were not taken consistently and were therefore scattered over the different sampling sites and times. To allow a uniform approach to all variables, data from replicate samples were averaged to arrive at combination. These a single mean data case for each site-period-year mean values were then analyzed for temporal and spatial variation. For study elements involving body burdens, desired samples were often not obtained due to failure to catch the species in question. For other the study elements (e.g. high-molecular-weight hydrocarbons in sediment), contracted samples involved one set of sites during one collection period but a different set of sites during other collection periods. Thus, for several variables the datawere scattered over the range of possible data cases. Even when samples were obtained, it was often the case that par- variables ticular variableswere uncalculable or unmeasurable. For example, uncalculable if involving hydrocarbon ratios {e.g. pristane/phytane) were 0. concentrations the concentration in the denominator was Trace metal sometimes unmeasurable due detection limit problems. were to When data cases were scattered over the possible collection sites and times or when there were missing data for some data cases, analyses and variation involved unbalanced data (f.e, unequal for temporal spatial techniques (involving simple comparison of means) are not useful with unbalanced data. When data are unbalanced, all effects (both main effects and interactions) are confounded (Kerlinger and Pedhazur, 1973; Rao, 1965; Searle, 1971). Consider the following example: 1 Design Design 2 Season Season 12 12 Transect I 10 10 Transect 12 10 II1010 II8 10 Numbers within the cells are numbers of data cases. Design 1 involves balanced data (equal cell frequencies) while Design 2 involves unbalanced data (unequal cell frequencies). The standard ANOVA technique for assess­ ing the season effect in such designs involves comparisons of the mean value for Season 1 with the mean value for Season 2. For Design 1, the Season 1 mean involves data cases which are equally divided between Transect I and 11, and the same is true for the Season 2 mean. Therefore, the difference between the Season 1 mean and the Season 2 mean is balanced with regard to transect. In Design 1, effects are unconfounded, and the standard ANOVA procedure of comparing row means and comparing column means is appropriate. For Design 2, the Season 1 mean involves data cases from Transect I 20% of the time and data cases from Transect II 80% of the time. The Season 2 mean for this design involves equal numbers of Tran­ sect X and Transect II data cases. If transect does indeed have an effect, then this differential effect due to the two transects will produce a dif­ ference between the Season 1 mean and the Season 2 mean, regardless of all the effects (transect, and transect by season interaction) season, are confounded and standard ANOVA procedures are not valid. Multiple linear regression analysis is the technique suggested for analysis of unbalanced data (Kerlinger and Pedhazur, 1973; Rao, 1965; For Searle, 1971). the present data, multiple linear regression analysis was used to assess the effect of a factor with all other factors in the design covaried (statistically controlled). For example, for a two-way analysis involving transect and season, the transect effect was assessed with the season effect and the transect by season interaction covaried, the season effect was assessed with the transect effect and the transect by season interaction covaried, and the transect by season interaction was assessed with the transect effect and the season effect covaried. All regression analyses were calculated by using the "Regression Option" of subprogram ANOVA from the Statistical Package for the Social Sciences (Nie et dl, , 1975). Regression analysis with covaried effects was applied to all the variables reported in Table A-10 whether the data for those variables were balanced or unbalanced. Such uniform approach all data was quite a to satisfactory. For variables with unbalanced data, regression analysis with covaried effects was necessary for meaningful interpretation of results. For variables with balanced data, regression analysis with covaried effects produced exactly the same results and conclusions as standard ANOVA procedures would have (Searle, 1971), For most variables, there was an insufficient number of data cases to attempt a full four factor design simultaneously incorporating all four effects of interest (transect, station group, collection period, and year) To allow a uniform approach a series of two factor to all parameters, analyses were performed for each variable. Table A-7 presents the two factor analyses performed for those variables sampled according to the 12 station scheme, for those sampled according to the 25 station scheme, and for those sampled according to the 2 station scheme. For the 12 station scheme, all possible two factor analyses were performed. For the 25 station scheme, 5 of the 6 possible two factor analyses were performed. The transect by station analysis was not attempted for the 25 station sampling scheme. A glance at Table A-4 will demonstrate the difficulty in performing a transect by station analysis for the 25 station sampling scheme. The transects are haphazardly represented in the first three station depth groups. Note that there is no easy redefinition of these three station groups which would yield groups containing an equal number of representatives from each transect. Given this situation, the results of a transect by would have been quite difficult to station analysis interpret. For the two station sampling period, only three two-factor For the two station scheme, there was one analyses were performed. only spatial effect (transect). This one spatial effect with the two temporal effects (period and year) produced three possible two-factor analyses. Note that a significance level of P £ 0.05 was employed in all analyses for spatial and temporal effects. The following procedure was employed in order to lessen the probability of accepting a chance-pro­ duced significant result as a valid result. The overall 1? ratio for each two-factor analysis was examined. These overall F_f s are analogous to the overall between-groups F/s in standard ANOVA; they provide a single test of all effects (main effects and interaction) pooled together. If the overall _F for a specific two-factor analysis was not significant CP £ 0.05 level), then the entire set of results for that analysis was TABLE A-7 TWO FACTOR ANALYSES STRATEGY PERFORMED FOR VARIABLES SAMPLED ACCORDING TO DIFFERENT SAMPLING SCHEMES Sampling Scheme Analyses Performed 12 station scheme Transect (I-IV) by Station Group (1-3) Transect (I-IV) by Period (1-9) Transect (I-IV) by Year (1975-1977) Station Group (1-3) by Period (1-9) Station Group (1-3) by Year (1975-1977) Period (1-9) by Year (1975-1977) 25 station scheme Transect (I-IV) by Period (1-9) Transect (I-IV) by Year (1976-1977) Station Group (1-6) by Period (1-9) Station Group (1-6) by (1976-1977) Year Period (1-9) by Year (1976-1977) 2 ­ station scheme Transect (HR SB) by Period (1-9) Transect (HR SB) by Year (1976-1977) - Period (1-9) by Year (1976-1977) discarded as chance If the overall _F produced. was significant, then sig­ nificant main effects from that analysis were accepted as valid signifi­ cant results. In other words, a significant main effect was accepted as valid only if the corresponding overall F_ was also significant. The entire set of two-factor analyses a given was then for variable inspected. Only if a given effect (e.g year) was significant in every . two-factor analyses involving that effect, was that effect accepted as a clear source of significant variation. For example, consider a variable collected under the 12 station sampling scheme. Six two-factor analyses would be involved in this case and the year effect would be analyzed in three of the six analyses. If year were found to be significant in each of the three analyses, then year would be accepted as clearly significant. That is, year is significant when period is covaried, when station is covaried and when transect is covaried. If year were found to be signifi­ cant in only one or two of the three analyses, then the picture is unclear. The significant year effects in one or two of the analyses do indicate this significant variation, but clear identification of the source of variation is due to confounded effects. significant not possible If a main effect was accepted as being clearly significant for a then all interactions involving that main effect particular variable, were inspected for significance. A significant interaction involving a main effect indicated that the main effect may not be general. For example, consider a where the main effect of station is significant and the case station by transect interaction is also significant. The significant station main effect indicates that stations differ on the average. The transect interaction indicates that the difference significant station by among stations varies for the different transects. It is quite possible and IV. That is, the station effect may not be general with regard to transect. Because of such possibilities, significant main effects have been reported in Table A-10 only when there were no significant interactions involving those main effects. A few comments are necessary concerning these procedures for selection of spatial and temporal effects. For some variables, a limited number of data cases resulted in two-factor designs with empty cells. In these cases it was impossible to evaluate the two-way interaction. Also, for some trace metal body burden variables, data were not available for an entire spatial category (s,g, Transect II or Station Group 3) or any entire In such temporal category (e.g. spring). cases, these categories were omitted from analysis. In summary a spatial or temporal result was included in Table A-10 only if the answer to all of the following questions was yes. 1) Is the overall 1? significant for two-factor analysis every involving the main effect in question? 2) Is the main effect significant in each of the relevant two factor analyses? 3) Are the interactions involving the main effect all insignificant? This procedure for selecting the temporal and spatial results for inclu­ sion in Table A-10 served to limit the reported effects to those which were clear, general, and had the least probability of being chance produced. Comparison of the Present Baseline Results to Future Monitoring Pesults The t-test presents a simple method for comparing the present baseline results to Given the results obtained in future monitoring. a mean and standard deviation from the present baseline results and a mean and standard deviation from future monitoring, a t value can be computed as follows. ~ XM XB - ~ - STD ERR In expression [l], indicates the mean value for future monitoring; X B indicates the mean baseline value; and STD ERR indicates the appropriate standard error. The standard error in expression [l] is the standard error of the difference between the two means and this standard error is given as follows. * 7SS+SSM\ / B i\]STD ERR [2] - [\*rrW2) (w + %)l The terms [2] are as follows: SSindicates the sum of in expression B for the baseline results; SSm indicates the sum of for the squares squares monitoring results; Nindicates the number of data cases for the baseline B results; and 1% indicates the number of data cases for the monitoring results. The monitoring sum of squares is defined as follows. % 2 - = SSM 2 CXjyL-XM) i-1 The baseline sum of can be obtained from the standard deviation squares (STD DEV) in Table A-10 as follows. ~ SSB = (STD DEV)(NB 1) The t value in expression [l] is associated with a number of degrees of freedom (df) equal to Ng + -2, The significance of an obtained t can then be determined by reference to a t-table with the obtained t value and of freedom. the degree For convenience, a t-table has been reproduced here as Table A-8, is Comparison of baseline and monitoring results quite straightforward when the baseline results (Table A-10) do not include significant temporal and/or spatial variation. In this case, the t-test can be based upon the overall monitoring results. When the baseline results for a variable then determina­ indicate significant temporal and/or spatial differences, tion of baseline vs. monitoring differences is more complicated. If there is significant baseline variation due to collection period (-£,e. month or season), then baseline vs. monitoring comparisons should be performed sep­ arately for each collection period involved. If there is significant baseline variation due to collection site (i.e. station depth, or group should be made for each relevant transect), then separate comparisons spatial category. Determination of the Number of Samples Needed in Future Monitorin Suppose one wishes to determine if the value for a variable has changed significantly from the baseline value. How many monitoring samples (data cases) would be required? This "number of samples" issue falls within the realm of statistical of a power analysis. The power statistical test is the probability that it will yield significant results when a difference actually exists in nature. That is, statistical power is the probability of detecting a population difference in a statistical A-30 TABLE A-8 THE DISTRIBUTION OF t (2-Tailed Test)* Degrees of Freedom 0.500 Probability of a Larger Value, Sign Ignored 0.400 0.200 0.100 0.050 0.025 0.010 0.005 0.001 1 2 3 1.000 0.816 .765 1.376 3.078 6.314 12.706 25.452 63.657 1.061 1.886 2.920 4.303 6.205 9.925 14,089 31.598 0.978 1.638 2.353 3.132 4.176 5.341 7.453 12.941 4 5 .741 .727 .941 1.333 2.132 2.776 3.495 4.604 5.598 8.610 .920 1.476 2.015 2.571 3.163 4.032 4.773 6.859 5 / 8 9 10 .718 .711 .706 .703 .700 .906 1.440 1.943 2.447 2.969 3.707 4.317 5.959 .896 1.415 1.395 2.365 2.841 3.499 4.029 5.405 .889 1.397 1.860 2.306 2.752 3.355 3.832 5.041 ,883 1.383 1.333 2.262 2.685 3.250 3.690 4.781 .879 1.372 1,812 2.228 2.634 3.169 3.581 4.537 11 12 13 14 15 .697 .695 .694 .692 .691 .876 1.363 1.796 2.201 2.593 3.106 3.497 4.437 .873 1.356 1.782 2.179 2.560 3.055 3.428 4.318 .370 1.350 1.771 2.160 2.533 3.012 3,372 4.221 .868 1.345 1.761 2.145 2.510 2.977 3.326 4.140 .866 1,341 1.753 2.131 2.490 2.947 3.286 4.073 16 17 . 18 19 20 .690 .689 .688 .638 .637 .865 1.337 1.746 2.120 2.473 2.921 3.252 4.015 .863 1.333 1.740 2.110 2.458 2.898 3.222 3.965 .862 1.330 1.734 2.101 2.445 2.378 3.197 3.922 .861 1.328 1,729 2.093 2.433 2.861 3.174 3.883 .360 1.325 1.725 2.086 2.423 t 2.345 3.153 3.850 21 22 23 24 25 .686 .686 .685 .685 .684 .859 1.323 1.721 2.080 2.414 2.331 3.135 3.319 .858 1.321 1.717 2.074 2.406 2.319 3.119 3.792 .358 1.319 1.714 2.069 2.398 2.807 3.104 3.767 .857 1.318 1.711 2.064 2.391 2.797 3.090 3.745 .856 1.316 1.708 2.060 2.385 2.787 3.078 3.725 26 27 28 29 30 .684 .684 .633 .683 .683 .856 1.315 1.706 2.056 2.379 2.779 3.067 3.707 .355 1.314 1.703 2.052 2.373 2.771 3.056 3.690 .355 1.313 1.701 2.048 2.363 2.763 3.047 3.674 .854 1.311 1,699 2.045 2.364 2.756 3.038 3.659 .854 1.310 1,697 2.042 2.360 2,750 3.030 3.646 35 40 45 50 55 .682 .631 .680 .680 .679 .852 1.306 1.690 2.030 2.342 2.724 2.996 3.591 .851 1.303 1.634 2.021 2.329 2.704 2.971 3.551 .350 1.301 1,680 2.014 2.319 2.690 2.952 3.520 .849 1.299 1.676 2.008 2.310 2.673 2.937 3.496 .849 1.297 1.673 2.004 2.304 2.669 2.925 3.4/6 60 70 30 90 ICO .679 .678 .673 .678 .677 .343 1.296 1.671 2.000 2.299 2.660 2-915 3.460 .847 1,294 1.667 1.994 2.290­2,648 2.899 3.435 ,847 1.293 1.665 1.989 2.284 2.638 2.887 3.416 .846 1,291 1.662 1.986 2.279 2.631 2.873 3.402 .846 1.290 1.661 1.982 2.276 2.635 2.871 3.390 120 oa .677 .6745 .345 1.289 1.653 1.980 2.270 2.617 2.360 3.373 .8416 1.2316 1.6443 1.9600 2.2414 2,5758 2.8070 3.2905 *Adapted from Snedecor and Cochran (1967, Table A-4, p 549), of samples drawn from that population. For the present purposes, analysis we are concerned with the power of the t-test for means. The statistical power of the t-test is a complex function of the difference between the size population means, the level of significance chosen, the sample (number of data cases), and the measurement error. Consider the basic formula for the t-test. - X Xi 2 1= C3]—zr 2 SN In expression [3], Xi and X 2 refer to the means of the two S is groups, the pooled within groups standard deviation, and N is the sample size (number of data cases per group). The obtained value of t is significant if it exceeds a tabled critical value. The power of the t-test will increase if the calculated value of t increases or if the critical value decreases. Increasing the significance level (i,efrom 0.05 to 0,10) will. decrease the tabled critical value. Thus, the power of the t»test is a positive function of significance level. Note in expression [3] that the obtained t value is positively related - to the obtained mean difference (Xi X 2). The larger the difference in population means between the two the obtained mean groups, the larger difference will tend to be. Thus, the power of the t-test is a positive function of the population mean difference. The value of S in [3] is a positive function of measurement error. The obtained t in turn is inversely related to S. Therefore, the power of the t-test is a negative function of measurement error. The sample size (N) is directly related to the obtained t in expression [3]. The power of the t-test is therefore posi­ tively related to the sample size. A-32 For present purposes, it will be convenient to define the effect size (EF) as follows. - Xi X X2-X ®­ s— . In expression [4], X refers to the overall grand mean. The effect size in [4] is a measure of the standardized (normal deviate) difference between the two group means. The convenience of such an effect size is that it is independent of the specific units of measurement. Such an effect size can be used in constructing general tables which are appli­ cable to any variable regardless of units of measurement. Expression [4] can be simplified as follows. - x EF= [s] Xj 2 1 Expression [s] can then be substituted into expression [3] yielding: = t (EF)OD*. [6] Note that the obtained t-value is a function of in expression [6] positive the effect size. Thus, the power of the t-test is a function of positive effect size. Sufficient background has been provided to now consider a table of sample sizes based upon statistical power. the sample Table A-9 presents sizes required to obtain a significant difference with a given probability (power) for a given effect size (EF), To use Table A-9, one must choose a desired effect size, power, and level of significance. The level of TABLE A-9 SAMPLE SIZE TO DETECT EFFECT SIZE (EF) AT A GIVEN LEVEL OF POWER AND A GIVEN LEVEL OF SIGNIFICANCE* ai * . 01 (a 2 * .02) ** EF Power .10 .20 .30 .40 .50 .60 .70 .80 1.00 1 .20 1.40 .25 547 138 62 36 24 17 13 10 7 5 4 .50 1083 272 122 69 45 31 24 18 12 9 7 .60 1332 334 149 85 55 38 29 22 15 11 8 2/3 1552 382 170 97 62 44 33 25 17 12 9 .70 1627 408 182 103 66 47 35 27 18 13 10 .75 1803 452 202 114 74 52 38 30 20 14 11 .80 2009 503 224 127 82 57 42 33 22 15 12 .85 2263 567 253 143 92 64 48 37 24 17 13 .90 2605 652 290 164 105 74 55 42 27 20 15 .95 3155 790 352 198 128 89 60 51 33 23 18 .99 4330 1084 482 272 175 122 90 69 45 31 23 al a 05 (32 ¦ . 10) EF Power .10 .20 .30 .40 .50 ,60 .70 .80 1.00 1.20 1.40 .25 189 48 21 12 8 6 5 4 3 2 2 .50 542 136 61 35 22 16 12 9 6 5 4 .60 721 181 81 46 30 21 15 12 8 6 5 2/3 862 216 96 55 35 25 18 14 o 7 5 .70 942 236 105 60 38 27 20 15 10 7 6 .75 1076 270 120 68 44 31 23 18 11 8 6 .80 1237 310 138 78 50 35 26 20 13 9 7 .85 1438 360 160 91 58 41 30 23 15 11 8 .90 1713 429 191 108 69 48 36 27 18 13 10 .95 2165 542 241 136 87 61 45 35 22 16 12 .99 3155 789 351 198 127 88 65 50 32 23 17 *Adapted from Cohen, 1969, Table 2. 4.1, PP 52--53 **ai is the one-tailed level of significance; a 2 is the two--tailed level of significance TABLE A-9 CONT.’D ai = ..10 (a2 CN|o/ II . N EF Power .10 .20 .30 .40 .50 .60 .70 .80 1.00 1.20 1.40 74199 5332 2 .25 222 32982 37211410 7 5 4 3 .60 4711185330 191410 8 5 4 3 586147653724171210 6 4 3 .50 2 2/3 6531637341 27191411 7 5 4 .75 766192854831221613 8 6 4 .80 902226100 57 36 26 19 14 10 7 5 .85 1075269120 67 43 30 22 17 11 8 6 .70 .90 1314329146 82 53 37 27 21 14 10 7 .95 1713428191107 69 48 35 27 18 12 9 .99 2604 651 290 163 104 73 53 41 26 18 14 - 005 (a2 .01) EF • Power .10 .20 .30 .40 .50 .60 .70 80 1.00 1.20 1.40 .25 72518382473122 1713 9 7 6 .50 1329333 149 85 55 39 29 22 15 11 9 .60 1603 402 180 102 66 46 34 27 18 13 10 2/3 1810 454 203 115 74 52 39 30 20 14 11 .70 1924 482 215 122 79 55 41 32 21 15 12 .75 2108 528 236 134 86 60 45 35 23 17 13 .80 2338 586 259 148 95 67 49 38 25 18 14 .85 2611 654 292 165 106 74 55 43 28 20 15 .90 2978 746 332 188 120 84 62 48 31 22 17 .95 3564 892 398 224 144 101 74 57 37 26 20 .99 4808 1203 536 302 194 136 100 77 50 35 26 a­ ai 025 (a2 .05) . EF Power .10 .20 .30 .40 .50 .60 .70 80 1.00 1.20 1.40 .25 3328438221410 8 6 5 4 3 .50 769193864932221713 9 7 5 .60 981246110 62 40 28 21 16 11 8 6 2/3 1144287 128 73 47 33 24 19 12 9 7 .70 1235310 138 78 50 35 26 20 13 10 7 .75 1389348155 88 57 40 29 23 15 11 8 .80 1571393 175 99 64 45 33 26 17 12 9 .85 1797 450 201 113 73 51 38 29 19 14 10 .90 2102 526 234 132 85 59 44 34 22 16 12 .95 2600 651 290 163 105 73 54 42 27 19 14 .99 3675 920 409 231 148 103 76 58 38 27 20 one does not exist. Selection of significance level is straightforward and needs no discussion. Selection of effect size and are more power difficult and need to be considered in detail. The effect size of interest in the present appendix is based upon a difference between known baseline results and the unknown results of future monitoring. For this case, expression [s] can be rewritten as follows. b B In expression [7], and Xg are the monitoring and baseline means, while Sg is the baseline standard deviation. Note that before monitoring Sg is the best guess as to the value of the pooled within groups standard is deviation calculable after monitoring. Before monitoring, Xjf the only unknown value on the right side of expression [7]. If one can select a mean for monitoring which is a critical value to detect, then this desired effect value can be substituted into [7] thereby yielding the size for entry into Table A-9. For example, the XM chosen may be the critical value of a trace metal beyond which this metal is toxic in the aquatic environment. Another choice of a critical value for the may be one or two standard deviations below the Xg to use for example for benthos infaunal density or demersal fish density. One must then specify the level of confidence (power) for detecting a value as extreme as the critical value of This level of confidence is the probability of finding a difference when one exists and usually is greater than 0.80. Entry into Table A-9 with this confidence level (power) and effect size size in the will then yield the required sample (number of data cases) A-36 the table. body of Therefore, when selecting a sample size, the rule of thumb is to have level as low as a as a significance possible and power as high possible. The meeting of these two criteria, however, depends upon the economics of obtaining the information since by meeting the criteria you will dramatically increase your sample size. Unfortunately, one difficulty remains in using the sample size value obtained from Table A-9. The sample size values in this table are for a t-test involving two groups of equal size. Construction of sample size tables allowing unequal group sizes involves too much additional complex­ ity. The present sample size table can be adopted, however, to use with sizes unequal group in the manner suggested by Cohen (1969). For unequal sized groups, the same size values in Table A-9 should equal the harmonic mean of the two group sizes. The harmonic mean of the two group sizes (Ni and N2) is given by: 2NiN2 _ Nh=N +N x2 For our case involving baseline and monitoring results, this expression becomes: 2% % N[B] _ = h ¦ ...Nn %+m Now is the value from Table A-9 and Ng is the baseline sample size, a known value. Therefore, is the only unknown in [B] and this be solved for result. expression can with the following Nnhb [9l % 2N-NBh Expression [9] can then be used to estimate the required number of moni­ toring samples, given the value from Table A-9 and the known number of baseline data cases (Ng). One caution must be considered concerning the use of expression [9]. Note that the calculated value of Nj.j will be negative if the quantity, is less than zero. In this case, there is no possible value for and there is no to detect the chosen way effect size with the desired power. The only solution is to decrease the effect size of interest and/or decrease the power desired. Such difficulties arise because the number of baseline data cases is fixed and this number Imposes limits on the achievable level of power for a given effect size. In conclusion, statistical power analysis affords a method for estimating the number of samples needed in future monitoring. While the methods are complex and require the user to make subjective judgements about effect size and confidence, they do provide guidelines to assist in monitoring planning. No viable alternative exists. A-38 LITERATURE CITED Cohen, J. 1969. Statistical power analysis for the behavioral sciences. New York, Academic Press. Kerlinger, F. N., and E. J. Pedhazur. 1973. Multiple regression in behavioral research. New York, Holt, Rinehart, and Winston. Nie, N. H., C. H. Hull, J. G. Jenkins, K. Steinbrenner, and D. H. Bent. 1975. Stati stical pa ckage for the social sciences. New York, McGraw Hill. Rao, C. R. 1965. Linear statistical inference and its applications. New York, Wiley. Searle, S. R. 1971. Linear models. New York, John Wiley and Sons. Snedecor, G. W., and W. G. Cochran. 1967. Statistical methods. lowa State Univ. Press, Ames, lowa. INDEX OF VARIABLES FOR TABLE A-10* Page PELAGIC NON-LIVING CHARACTERISTICS HYDROGRAPHY Secchi Depth A-45 NUTRIENTS-SURFACE Silicate A-45 Phosphate A-46 Nitrate A-46 Dissolved Oxygen A-46 LOW-MOLECULAR-WEIGHT HYDROCARBONS-SURFACE Methane A-46 Ethene A-47 Ethane A-47 Propene A-48 Propane A-49 NUTRIENTS-HALF PHOTIC ZONE Silicate A-49 Phosphate A-50 Nitrate A-50 Dissolved Oxygen A-50 LOW-MOLECULAR-WEIGHT-HYDROCARBONS-HALF PHOTIC ZONE A-50 Ethene A-50 Ethane A-51 Propene A-51 Propane A-51 Methane HIGH-MOLECULAR-WEIGHT HYDROCARBONS Dissolved Total Hydrocarbons A-52 Pristane vs. Phytane A-52 Particulate Total Hydrocarbons A-52 Phytane vs. n-Cis A-53 Sum Mid A-53 NUTRIENTS-BOTTOM A-53 Silicate Phosphate A-54 Nitrate A-55 Dissolved Oxygen A-55 A-40 INDEX CONT.’D LOW-MOLECULAR-WEIGHT HYDROCARBONS-BOTTOM Methane Ethene Ethane Propene Propane PELAGIC LIVING CHARACTERISTICS PHYTOPLANKTON-SURFACE Phytoplankton Species Phytoplankton Density Chaetoceros spp. Nanno C 11+ 1H Net C llf Total C Nanno Chlorophyll Net Chlorophyll Total Chlorophyll Nanno Phaeophytin Net Phaeophytin Total Phaeophytin PHYTOPLANKTON-HALF PHOTIC ZONE Phytoplankton Species Phytoplankton Density Nanno Chlorophyll Net Chlorophyll Total Chlorophyll Nanno Phaeophytin Net Phaeophytin Total Phaeophytin PHYTOPLANKTON-BOTTOM Total Chlorophyll Total Phaetophytin ZOOPLANKTON Copepod Species Number Copepod Total Density Ichthyoplankton Density Total Zooplankton Biomass Fccrranula gracilis Clausocalanus jobei Nannocalanus minor Page A-56 A-56 A-57 A-57 A-57 A-58 A-58 A-58 A-58 A-58 A-59 A-59 A-59 A-59 A-60 A-60 A-61 A-61 A-61 A-62 A-62 A-62 A-62 A-62 A-63 A-63 A-63 A-63 A/ A-64/ A // A-64 A tL! A-64 A-64 A-65 A-65 INDEX CONT. r D Page ZOOPLANKTON cont.’d Oncaea mediterranea A-66 Paraoalanus aouleatus A-66 Temora turhinata A-66 Paraoalanus indicus A-66 Paraoalanus quasimodo A-67 Centropages velifioatus A-67 Total Calanoids A-68 Larvaeea A-68 Total Cladocera A-68 HIGH-MOLECULAR-WEIGHT HYDROCARBONS Zooplankton Total Hydrocarbons A-69 Pristane vs. Phytane A-69 Pristane vs. n-Ci? A-69 Phytane vs. n-Cia A-69 (Pr+Ph)/n-alkanes A-69 SUM LOW A-69 SUM MID A-70 SUM HIGH A-70 Average OEP A-70 TRACE METALS Zooplankton Iron A-70 Calcium A-70 Vanadium A-70 Zinc A-71 Aluminum A-71 Lead A-71 Nickel A-71 Copper A-71 Chromium A-71 Cadmium A-71 BENTHIC NON-LIVING CHARACTERISTICS SEDIMENT TEXTURE Sediment Mean Grain Size A-72 Sediment Grain Size Standard Deviation A-72 Percent Sand A-73 Percent Silt A-74 Percent Clay A-74 A-42 INDEX CONT.'D Page SEDIMENT CHEMISTRY Sediment Total Organic Carbon A-75 13 A-75Sediment Delta C HIGH-MOLECULAR-WEIGHT HYDROCARBONS Sediment Total Hydrocarbons A-76 Pristane vs. Phytane A-77 A-77 Pristane vs. n-Ci? Phytane vs. n-Cxa A-77 (Pr+Ph)/n-alkanes A-77 SUM LOW A-77 A-77 SUM MID A-78 SUM HIGH BENTHIC LIVING CHARACTERISTICS MICROBIOLOGY Fungal Counts A-79 Fungal Oil Degraders A-79 A-79 Total Bacteria Bacteria Oil Degraders A-79 MEIOFAUNA Total Meiofauna Species A-79 Total Meiofauna Density A-80 Nematode Density A-81 Harpacticoid Density A-81 MACROINVERTEBRATES A-82 Infauna Species Infauna Density A-83 Epifauna Species A-83 A—83 Epifauna Density DEMERSAL FISHES Fish Species A-84 Fish Density A-84 A-84 Fish Biomass HIGH-MOLECULAR-WEIGHT HYDROCARBONS Penaeus aztecus Total Hydrocarbons A-84 INDEX CONT.’D Page Lutjanus campeohanus Total Hydrocarbons-gonad A-84 Total Hydrocarbons-gill A-85 Total Hydrocarbons-liver A-85 SUM MID-liver A-85 Average OEP-liver A-85 Total Hydrocarbons-muscle A-86 Rhomboplites aurorubens Total Hydrocarbons-gill A-86 Total Hydrocarbons-gonad A-86 Total Hydrocarbons-muscle A-86 Total Hydrocarbons-liver A-86 Pristane vs. n-C 17-liver A-87 Traohurus lathami Total Hydrocarbons A-87 Stenotomus oaprinus Total Hydrocarbons A-87 Loligo pealed Total Hydrocarbons A-88 Serranus atrobranehus Total Hydrocarbons A-88 Pristipomoides aquilonaris Total Hydrocarbons A-88 TRACE METALS Body Burdens Penaeus azteous-flesh Zinc A-88 Cadmium A-89 Traohurus lathami-flesh Cadmium A-89 Calcium A-89 Aluminum A-89 Serranus atrobranehus-flesh Zinc A-89 A-44 INDEX CONT.'D Page Stenotomus oaprinus-flesh Cadmium A-89 Luteanus oampeohanus-gill Vanadium A-90 *The analytic methods used to determine the values for the variables presented in Table A-10 are detailed in Volume III, 24 2424 3636 242424 M 108 108 Cl 6.80 6.00 4.80 2.80 36.00 21.00 34.00 39.00 35.00 39.00 P1R EM--­ 95% -­ 2.002.00 --2.000.160.700.40 -5.009.005.000.16 -­ 0.24 1.28 3.46 0.59 KURT -0.46 1.77 -0.03 -1.03 -0.07 -0.59 SKEW 0.47 1.49 0.85 0.20 0.05 1.06 1.66 0.68 0.92 0.32 DEV 9.59 5.10 7.83 7.39 9.24 8.60 1.68 1.38 1.25 0.66 STD 2.32 2.47 2.07 1.43 MEAN 15.93 6.83 16.13 22.71 18.42 12.03 12 3 123 CHARACTERISTICS liter) Group Group Group Group Group Group DEPTH Station Station Station 1976 1977 Station Station Station NON-LIVING SECCHI (meters) SILICATE (surface) (micromoles/ PELAGIC HYDROGRAPHY (1976-1977) NUTRIENTS (1976-1977) A-46 N 105 108 36 36 36 36 36 108 144 Cl 0.56 1.90 6.36 275.00 377.00 260.00 240.00 240.00 157.00 EMPIR - -- - 0.01 0.05 4.26 95% 41.00 40.00 37.00 45.00 37.00 41.00 KURT -0,15 29.94 1.33 25.30 4.27 11.28 9.86 10.93 4.08 SKEW 0.93 4.98 1.15 4.33 2.12 3.03 2.70 2.83 1.89 DEV 0.16 0.51 0.53 STD 64.96 77.73 41.63 36.20 36.17 24.79 MEAN 0.19 0.29 5.10 89.47 106.86 73.14 81.28 78.11 68.42 CHARACTERISTICS /liter) HYDROCARBONS iter) /I OXYGEN 1975 1976 NON-LIVING (cont.'d) PHOSPHATE (surface) (micromoles/llter) NITRATE(surface) (micromoles DISSOLVED (surface) (milliliters METHANE (surface) (nannoliters/liter) Winter Spring Fall LOW-MOLECULAR-WEIGHT DISSOLVED (1975-1977) PELAGIC NUTRIENTS N 36 363636 363636 352336 144 130 Cl 7.5 1.8 3.5 0.5 1.6 25.3 58.3 25.0 58.3 19.1 10.0 377.0 -— EMPIR - 95% 1.5 0.2 2.3 2.9 1.5 0.2 1.9 0.1 0.1 0.2 0.1 44.0 KURT 2.69 0.01 7.31 0.46 5.53 3.51 8.92 2.83 1.04 3.59 17.99 -0.27 SKEW 1.77 3.64 0.67 2.60 0.96 2.18 0.77 1.64 2.56 1.54 0.73 1.91 DEV 81.07 7.46 1.65 11.87 5.50 12.06 4.99 1.72 0.51 0.74 0.07 0.36 STD 7.08 3.33 9.50 7.27 4.15 0.56 0.95 0.34 0.39 MEAN 10.62 12.02 114.75 CHARACTERISTICS HYDROCARBONS 1977 Winter Spring Fall 1975 1976 1977 Winter Spring Fall NON-LIVING ETHENE (surface) (nannollters/liter) ETHANE (surface) (nannoliters/liter) *d) LOW-MOLECULAR-WEIGHT PELAGIC (cent, A-48 N 243535 363534 353634 33 3636 141 Cl 3.5 0,7 0.9 4.3 5.7 4.2 4.6 1.8 5.7 4.4 5.7 1.9 2.0 EMPIR ---— 95% 0.1 0,1 0,1 0.4 0.5 0.5 0.2 0.2 0.9 0.8 0.2 0.4 0.4 KURT 0.35 1.41 5.77 3.75 3.26 5.72 5.06 2.45 -0.30 -0.04 -0.05 -0.46 -0.04 SKEW 0.52 1.07 0.52 2.02 1.99 1.47 1.85 0.84 2.22 1.66 0.74 0.24 -0.71 DEV 0.90 0.14 0.20 0.88 1.15 0.80 0.85 0.41 1.06 0.91 1.39 0.42 0.38 STD MEAN 1.13 0.35 0.44 1.43 1.74 1.41 1.31 0.83 1.87 1.77 2.14 1.35 1.03 CHARACTERISTICS HYDROCARBONS 12 3 1975 1976 1977 Station Station Station Winter Spring Fall 1976 1975 1977 NON-LIVING PROPENE (surface) (nannoliters/liter) ’d) LOW-MOLECULAR-WEIGHT PELAGIC (cont. 353235 31 3635 242424 N 138 108 Cl 3.2 4.1 1.3 4.7 4,7 0.8 0.7 6.80 6.20 3.40 2.60 EMPIR 95% 0,1 0.3 0.1 0.2 0.1 0.2 0.2 0.15 0.15 0.70 0.50 KURT 8.80 3.07 0.73 3.27 0.05 3.36 0.74 -0.96 0.12 11.22 -0.07 SKEW 2.90 2.97 1.52 1.38 0.74 1.32 0.24 1.71 0.73 0.32 0.90 DEV 0.80 0.73 0.26 1.26 1.23 0.12 0.13 1.60 1.42 0.85 0.58 STD MEAN 0.72 0.83 0.47 1.14 1.73 0.42 0.43 2.18 2.50 1.85 1.27 123 CHARACTERISTICS HYDROCARBONS zone)Group Group Group Winter Spring Fall 1975 1976 1977 Station Station Station NON-LIVING PROPANE (surface) (nannoliters/liter) (half-photic (micromoles/liter) SILICATE ’d) LOW-MOLECULAR-WEIGHT (cont. NUTRIENTS (1976-1977) PELAGIC A-50 N 242424 96 107 108 114 107 Cl 4.50 2.50 6.20 0.67 1.80 6.35 22.20 393.00 EMPIR ­ - 0.15 0.80 0.50 0.01 0.05 4.47 1.70 95% 42.00 KURT 0.30 1.74 8.03 2.82 7.40 -0.94 34.46 75.52 SKEW 0.81 0.66 0.99 2.32 5.50 1.47 8.44 2.46 DEV 1.08 0.59 1.33 0.19 0.46 0.46 473.90 4.86 STD MEAN 1.85 1.37 2.40 0.17 0.24 5.10 6.16 155.56 zone)zone)zone) zone) zone) CHARACTERISTICS OXYGEN s/liter) HYDROCARBONS s/liter) photic photic NON-LIVING (cont.'d) Winter Spring Fall PHOSPHATE (half-photic (micromoles/liter) NITRATE (half-photic (micromoles/liter) DISSOLVED (half-photic (milliliter METHANE (half (nannoliter ETHENE (half (nannoliters/liter) LOW-MOLECULAR-WEIGHT DISSOLVED (1975-1977) PELAGIC NUTRIENTS 243624 36 1236 80 24 1224 89 88 N Cl 2.2 3.0 0.8 2.2 3.7 4.0 PIR 11.8 22,2 30.0 30.0 11.0 11.0 T . r EM --------_ - ,, 95% 1*3 1.7 2,3 1,3 1,7 1,9 0.1 0.5 0.2 0.1 0.2 0.01 KURT 2.17 3.38 1.75 4.93 1.70 1.50 0.00 2.00 3.79 2.72 10.02 -1.15 SKEW 2.74 1.47 1.95 1.43 0.42 1.94 1.43 1.04 0.99 1.79 1.80 1.89 DEV 2.09 4.53 7.23 6.85 2,90 1.93 0.61 0.62 0.18 0.67 0.89 1.08 STD MEAN 3.65 7,10 8.24 8.98 5.86 4.10 0.72 1.17 0.44 0.55 1.30 0.98 CHARACTERISTICS HYDROCARBONS zone)zone)zone) photic Spring photic photic Winter Spring Fall 1975 1976 1977 Winter Fall NON-LIVING ETHANE (Half(nannoliters/liter) PROPENE (half (nannoliters/liter) PROPANE (half(nannoliters/liter) 'd) LOW-MOLECULAR-WEIGHT PELAGIC (cont. A-52 N 242124 40 14 4 18 125 103 Cl 4.7 1.3 4.2 0.91 7.17 28.00 6.75 3.50 1.61 EMPIR 95% -----­ 0.4 0.01 0.2 0.000.122.000.120.310.00 KURT 9.96 1,35 3.27 4.50 -1.66 72.75 31.10 -0.97 10.80 SKEW 2.81 0.88 0.31 7.82 5.33 1.81 1.73 0.10 3.34 DEV 0.93 0.31 1.51 0.53 4.34 12.18 1.50 1.00 0.36 STD MEAN 1.08 0.49 1.77 0.22 2.73 2.12 1.72 0.18 10.04 CHARACTERISTICS HYDROCARBONS HYDROCARBONS ram PHYTANE 2) 3 n-Caz) /gram) g n-C HYDROCARBONS ) HYDROCARBONS to to Winter Spring vs. Winter Spring Fall g o r Fall NON-LIVING TOTAL (n-Cm rams PRISTANE TOTAL (n-Cut (microgramsic d) (m 1 LOW-MOLECULAR-WEIGHT HIGH-MOLECULAR-WEIGHT (1975-1977) / PARTICULATE (1975-1977) DISSOLVED PELAGIC (cont. 40 31716 242635 90 618 N 101 Cl 2,41 0.10 0.45 2.41 75.80 65.54 88.38 73.33 7.60 4.63 6.70 EMPIR - 95% 0,03 0.07 0,03 0.09 0.00 0.00 0.000.00-0.40 0.30 0.80 KURT 34,88 0.00 0.54 1.04 0.80 -1.14 4.25 10.21 -0.23 -0.54 -1.51 SKEW 5.75 1,72 1.26 1,26 1.30 0.02 2.19 2.80 0.61 0.63 0.30 DEV 2,21 0.02 0,13 0,67 21.71 19.60 22.70 13.70 2.06 1.58 2.10 STD MEAN 0.83 0.08 0.18 0.83 22.91 32.80 19.94 14.03 3.70 2.24 3.63 12 CHARACTERISTICS HYDROCARBONS n-Ci C2 Group Group 1+ 8 percent) to 1975 1976 1977 n— Winter Spring Fall Station Station NON-LIVING )(relative (micromoles/liter) PHYTANE MID (n-Ci9 SILICATE (bottom) SUM 'd) HIGH-MOLECULAR-WEIGHT (cont. vs. NUTRIENTS (1976-1977) PELAGIC A-54 6 66 N 18 1212 1818 1818 89 17 18 12 12 Cl 9.98 7.54 4.20 7.80 7.60 9.98 7.54 5.81 1.88 0.43 1.34 0.67 0.38 1.19 4.74 EMPIR 95% 0.80 1.33 0.40 3.30 0.30 1.60 0.97 0.40 0.03 0.11 0.03 0.03 0.10 0.02 0.17 KURT 2,33 1,26 -0.59 -1.76 -1.07 -0,58 0.17 1.13 26.30 -2.52 6.09 0.96 -2.01 6.55 7.53 SKEW 1.42 0.98 -0.26 0.15 -0.09 0.60 0.68 0.78 4.40 -0.11 2.17 1.21 0.57 2.36 2.58 DEV 2.28 2.25 1.17 1.72 2.26 2.45 1.77 1.30 0.62 0.14 0.30 0.17 0.12 0.31 1.23 STD MEAN 3.57 3.66 2.64 5.48 4.00 4.60 3.49 2.50 0.48 0.28 0.38 0.25 0.23 0.30 1.16 6 345 123456 I II IV CHARACTERISTICS Group Group Group Group Group Group Group Group Group Group 'd) Station Station Station Station Transect Transect Transect Transect Station Station Station Station Station Station NON-LIVING (cont. III PHOSPHATE (bottom) (micromoles/liter) PELAGIC NUTRIENTS 81 90 6181861212 242424 3636 N 5.86 5.86 6.00 5.83 5.43 5.37 5.61 6.00 5.43 5.47 5.71 6.00 Cl 17.10 EMPIR - 95% 2.58 -2.58 -2.58­ 0.10 2.323.063.703.98 2.662.80 2.32 2.32 3.37 KURT 2.01 -0.78 -0.18 -0.66 -0.37 -0.61 -0.81 -0.07 0.60 0.01 -0.02 -1.25 -1.00 SKEW 1.75 -0.50 -0.99 -0.24 -0.14 0.12 -0.52 0.95 -1.35 -0.84 -0.71 -0.36 -0.05 DEV 5.48 0.95 1.35 0.82 0.57 0.52 0.91 0.96 1.00 0.82 0.75 1.01 0.73 STD MEAN 3.64 4.43 4.53 4.75 4.83 4.71 4.21 3.58 4.98 4.24 4.17 4.16 4.76 1 23456 CHARACTERISTICS Group Group Group Group Group Group OXYGEN Station Station Station Station Station Station Winter Spring Fall 1976 1977 NON-LIVING NITRATE (bottom) (micromoles/liter) DISSOLVED (bottom) (milliliters/liter) (cont.'d) PELAGIC NUTRIENTS N 88 89 618186 12 12 242424 ' Cl 8.1 5.6 6.5 1.9 4.0 6.4 589.0 10.5 11.8 18.6 18.6 -- EMPIR - - 95% 45.0 0.1 2.4 1.9 0.7 2.2 1.0 0.1 0.1 0.7 0.8 KURT 3.85 13.63 -0.73 7.01 8.53 2.86 3.17 -0.18 -0.48 0.79 4.38 SKEW 1.87 2.98 1.05 2.41 2.77 1.06 1.72 0.08 0.08 1.89 -0.07 DEV 2.63 2.33 2.29 4.11 1.11 1.53 0.51 1.04 1.29 4.08 150.89 STD MEAN 3.25 4.36 4.19 4.49 3.61 2.58 1.09 2.12 3.21 5.01 190.40 123456 CHARACTERISTICS HYDROCARBONS Group Group Group Group Group Group Station Station Station Station Station Station Winter Spring Fall NON-LIVING METHANE (bottom) (nannoliters/liter) ETHENE (bottom) (nannoliters/liter) LOW-MOLECULAR-WEIGHT DISSOLVED (1975-1977) PELAGIC N 66 89 88 1817 1212 88 CX 1.0 1.5 1.5 1.5 1.0 0.7 0.8 0.4 1.0 EMPXR -­ 95% 0.1 0.2 0.6 0.5 0.3 0.3 0.3 0.2 0.3 KURT 3.11 0.26 3.09 2.71 -0.15 -0.28 -0.78 -0.97 -0.11 SKEW 1.26 0.84 0.46 1.61 1.40 -0.93 -0.17 -0.48 -0.64 DEV 0.25 0.35 0.38 0.30 0.18 0.13 0.13 0.06 0.17 STD MEAN 0.54 0.65 1.16 1.01 0.62 0.51 0.48 0.32 0.52 56 1234 CHARACTERISTICS HYDROCARBONS Group Group Group Group Group Group Station Station Station Station Station Station NON-LIVING ETHANE (bottom) (nannoliters/llter) PROPENE (bottom) (nannollters/liter) PROPANE (bottom) (nannoliters/liter) 'd) LOW-MOLECULAR-WEIGHT PELAGIC (cont. A-58 N 107 17181818 51 51 107 107 67.00 11.71 11.89 Cl 963392.00 30200.00 30200.00 26720.00 8017,00 127400.00 EMPIR - 95% 5.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 400.00 KURT 0.04 50.57 63,51 1.27 10.51 6.76 6.62 1.28 1.80 SKEW 0.69 6.63 7.52 1.48 3.10 2.63 2.73 1.25 1.66 3.33 3.52 DEV ,15.94 261934.61 20848.99 10107.56 6590.06 2119.01 3583.39 STD 3.20 2.38 28.94 MEAN 83613.38 5283.28 7147.24 3052.33 1157.39 1509.11 /hr) /hr) SPECIES species/liter) DENSITY cells/llter) IIIIIIV 3 3 spp. I /ra /m CHARACTERISTICS ofof ** 1 Transect Transect Transect Transect c c C 14 C LIVING PHYTOPLANKTON (surface) (number PHYTOPLANKTON (surface) (number Chaetooeros (surface) (cells/liter) NANNO (surface) (milligrams (surface) (milligrams NET PHYTOPLANKTON (1976-1977) PELAGIC N 53 107 107 242423 242423 107 19.06 1.59 1.93 1.26 0.28 0.41 2.77 2.20 2.00 2.31 cx EMPIR --— — —---­ 95% 0,00 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.00 0.15 1.09 4.41 11.82 1.81 3.60 8.44 3.43 1.06 2.31 2.85 KURT 1.21 1.84 3.32 1.58 1.87 3.10 1.95 1.39 1.36 1.82 SKEW 5.37 0.35 0.42 0.37 0.08 0.12 0.66 0.57 0.35 0.58 DEV STD 4.99 0.45 0.19 0.33 0.05 0.04 0.64 0.80 0.43 0.58 MEAN 3 /hr) Group Group Group c CHARACTERISTICS CHLOROPHYLL 1 2 CHLOROPHYLL " l (cont.'d) 3/m CHLOROPHYLL 1igrams Station Station Station Winter Spring Fall C (surface) (mil (surface)(micrograras/liter) (surface) (micrograms/liter) (surface) (micrograms/liter) LIVING TOTAL NANNO TOTAL PELAGIC PHYTOPLANKTON A-60 N 242423 242423 3635 242423 107 107 Cl 1,47 1.93 1.42 1.44 1.44 1.45 1.93 1.44 1.93 1.67 2.00 1.67 1.60 EMPXR ---—-—--­ 95% 0.00 1.18 0.00 0.00 1.06 0.00 1.06 0.00 1.11 0.00 0.00 0.00 0.00 KURT 7.69 9.29 16.63 7.09 0.81 3.77 6.80 6.72 10.48 -1.85 0.04 -2.02 3.89 cs 2.55 2.14 2.39 0.29 0.25 2.36 SKEW -2.72 -3.80 -2.76 -0.80 -2.72 -1.27 CNl 1 0.34 0.15 0.28 0.37 0.09 0.44 0.19 0.36 0.14 0.75 0.65 0.74 0.54 DEV STD 1.20 1.35 1.21 1.13 1.31 1.11 1.26 1.13 1.33 0.66 1.20 0.66 0.20 MEAN 123 123 d) Group Group Group Group Group Group f CHARACTERISTICS (cont. PHAEOPHYTIN (micrograms/liter) Station Station Station Winter Spring PHAEOPHYTIN (micrograms/liter) Station Station Station Fall 1976 1977 LIVING NANNO (surface) NET (surface) PELAGIC PHYTOPLANKTON N 3635 3635 36 36 242424 107 108 108 2.00 1.75 1.52 1.47 1.85 68.00 73.00 45.00 Cl -478729.00 -478729,00 -125105.00 -407685.00 EMPIR - 95% 0.00 0.00 0.00 0.00 1.11 3.00 13.00 2.00 60.00 60.00 5660.00 2260.00 KURT 0.05 -1.41 7.27 6.29 4.27 0.37 0.18 -0.78 20.94 10.40 13.46 21.08 SKEW 1.35 -0.76 -2.67 -2.61 1.15 0.71 0.70 0.12 4.44 2.95 3.42 4.50 DEV 0.66 0.72 0.35 0.37 0.13 14.82 13.81 11.87 177591.70 102835.75 25451.93 82587.35 STD 0.37 1.03 1.22 1.15 28.18 34.67 23.14 MEAN 1.36 71671.67 73766.33 19573.38 30797.75 SPECIES DENSITY specles/liter) zone) zone) CHARACTERISTICS of (cont.'d) 1976 1977 PHAEOPHYTIN 1976 1977 photic 1976 1977 photic Winter Spring Fall LIVING TOTAL (surface) (micrograms/liter) PHYTOPLANKTON (half (number PHYTOPLANKTON (half(cells/liter) PELAGIC PHYTOPLANKTON A-62 N 24 24 3636 108 108 108 108 108 24 1.51 1.46 2.75 1.46 1.80 1.67 2.50 2.00 1.60 2.50 Cl EMPIR --—— 95% 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 KURT 6.52 10.62 4.45 5.17 -1.63 -0.62 -0.40 1.11 0.07 -1.47 SKEW 2.07 3.15 2.09 -2.54 0.42 -1.15 1.04 1.67 1.42 -0.34 0.38 0.36 0.67 0.38 0.77 0.68 0.80 0.66 0.63 0.79 DEV STD 0.46 0.17 0.63 1.16 0.65 1.14 0.54 0.33 0.33 1.00 MEAN 123 zone)zone)zone)zone) liter) zone)Group Group Group CHARACTERISTICS (cont.M) CHLOROPHYLL photic CHLOROPHYLL photic CHLOROPHYLL photic PHAEOPHYTIN photic photic PHAEOPHYTIN Station Station Station 1976 1977 (micrograms/liter) (micrograms/liter) (micrograms/liter) (micrograms/ (micrograms/liter) LIVING NANNO (half NET (half TOTAL (half NANNO (half NET (half PHYTOPLANKTON PELAGIC 90 6181861212 90 N 108 144 1,51 2.18 2.12 2.63 1.32 1.02 0.58 0.59 1.50 83.00 Cl EMPXR 95% 0.00 0.00 0.23 0.24 0.11 0.38 0.00 0.00 0.00 15.00 KURT 6.87 4.03 -1.38 0.78 -0.86 0.74 0.12 0.08 5.38 -0.85 1.65 0.88 0.33 0.84 0.75 0.57 SKEW -2.76 -0.52 -0.10 -2.53 DEV 0.36 0.65 0.73 0.59 0.35 0.24 0.17 0.19 0.39 20.47 STD 1.20 0.75 1.29 1.21 0.70 0.62 0.32 0.18 1.19 41.03 MEAN 123456 /m NUMBER) Group Group Group Group Group Group CHARACTERISTICS zone)3species SPECIES of (cont.'d) PHAEOPHYTIN photic(micrograms/liter) CHLOROPHYLL (micrograms/liter) Station Station Station Station Station Station PHAEOPHYTIN (micrograms/liter) LIVING TOTAL (half TOTAL (bottom) TOTAL (bottom) COPEPOD (number PHYTOPLANKTON ZOOPLANKTON (1975-1977) PELAGIC A-64 N 363636 363636 363636 144 144 144 144 70.60 97.90 Cl 1768,10 3594.10 1230.10 977.60 6209.00 5056.50 5975.00 8932.00 105.60 129.40 248.70 EMPIR 95% 91,30 47.00 56.40 107.40 75.00 32.00 329.50 361.00 3.30 0.00 0.00 0.00 0.00 KURT 15.62 5.58 0.01 4.07 1.92 5.20 -0.25 2.82 2.33 18.84 34.87 1.59 23.32 3,28 2.18 0.69 1.63 1.33 1.90 0.99 1.34 1.64 3.84 5.87 1.63 4.48 SKEW DEV 470.40 742.39 273.77 176.03 1741.02 1044.07 1694.90 1804.82 16.83 34.78 21.49 27.14 42.78 STD MEAN 535.94 816.54 478.14 331.37 2091.28 1000.29 2254.28 2829.04 21.84 17.38 4.94 18.59 22.52 ) 33 ) BIOMASS 12 123 3 DENSITY DENSITY individuals/m ra 3 Group Group Group Group Group Group CHARACTERISTICS larvae/1000 gracilis ’d) TOTAL ZOOPLANKTON ) of of3) (cont. Station Station Station Winter Spring Fall Station Station Station LIVING COPEPOD (number ICHTHYOPLANKTON (number (grams/m Farranula (individuals/m TOTAL PELAGIC ZOOPLANKTON N 363636 363636 363636 363636 144 144 19.85 79.15 248.70 85.50 76.05 75.95 342.55 16.75 12.30 17.05 26.15 20.60 12.30 26.15 cx EMPIR 95% 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 KURT 5.98 13,74 10.34 37.44 13.30 3.68 10.16 3.86 9.49 2.28 2.08 0.56 2.72 7.95 2.46 3.42 2.79 5.59 3.59 2.19 3.13 1.90 3.00 1.61 1.54 1.15 1.76 2.74 SKEW DEV 4.53 15.08 48.44 42.77 15.63 22.18 76.31 4.90 2.67 4.46 6.40 5.55 3.12 5.73 STD 2.54 8.61 5.81 3.51 1.16 3.75 5.73 5.39 2.37 2.88 34.91 16.28 11.92 40.09 MEAN 123 )) jobei minor Group Group Group 3 1s/ra idua CHARACTERISTICS (cont.’d) Winter Spring Fall (individuals/m 1975 1976 1977 Station Station Station Winter Spring Fall iv Clausooalanus Nannoaalanus LIVING (ind PELAGIC ZOOPLANKTON A-66 N 363636 363636 363636 144 144 144 144 CX 65.65 19.90 100.75 121.90 122.65 57.85 73.35 219.05 316.00 689.90 172.45 47.40 634.50 EMPIR -- 95% 0.00 0.00 0.00 1.55 0.00 0.65 0.500.000.000.00 0.000.000.00 KURT 6.51 13.23 10.49 3.81 14.79 0.89 9.96 7.43 31.26 10.11 12.17 8.21 12.92 2.20 3.31 2.74 1.62 3.32 1.18 2.74 2.54 5.18 3.11 3.35 2.82 3.32 SKEW DEV 21.11 3.88 19.38 25.70 31.78 14.03 14.07 47.15 86.90 145.84 34.74 10.71 157.24 STD 1.88 5.93 15.45 14.48 32.48 23.19 16.47 11.79 38.88 34.59 83.48 20.33 81.44 MEAN - 123 123 )))) 333 3 Group Group Group aouleatus Group Group Group indlous d) s/m CHARACTERISTICS mediterranea turbinata ! (cont, Station Station Station idual Winter Spring Fall Station Station Station iv LIVING Oncaea (individuals/m Paraoalanus (ind Temora (individuals/m Paraoalanus (individuals/m PELAGIC ZOOPLANKTON N 363636 363636 363636 363636 144 144 CX 688.45 192.60 203.35 674.25 688.45 634.50 486.45 490.35 160.25 102.30 150.65 206.05 220.50 27.30 EMPIR ---— 95% 0.00 0.00 0.15 0.80 0.00 0.00 0.00 0.00 1.05 0.00 0.00 0.00 0.00 0.00 KURT 0.39 -0.06 27.67 4.99 6.60 33.28 47.32 0.76 0.14 13.15 22.85 8.68 14.28 10.11 1.29 0.91 5.03 2.09 2.67 5.68 5.97 1.20 0.98 3.58 4.63 2.87 3.88 3.11 SKEW DEV 215.82 54.07 34.37 149.73 160.64 105.48 161.39 139.48 43.18 20.84 34.66 43.98 49.21 5.73 STD 55.83 14.60 85.54 30.14 77.01 48.51 11.64 13.83 27.19 17.94 MEAN 169.81 124.55 137.13 2.89 123 123 123 ) ) 33 Group Group Group quasimodo Group Group Group velifioatus Group Group Group s/m s/m CHARACTERISTICS *d) (cont, Station Station Station Winter Spring Fall idual Station Station Station idual Station Station Station iv iv LIVING Paraoalanus (ind Centropages(ind PELAGIC ZOOPLANKTON A-68 N 363636 363636 363636 144 144 144 CX 37.60 2860.20 5211.85 1411.05 1040.20 196.30 119.65 277.35 176.35 232.45 545.20 249.85 EMPIR - 95% * 61,20 55.85 61.20 67,75 1.75 1.20 2.25 2.05 0.00 0.00 0.00 0.00 2A 6.60 0.51 7.72 5.90 7.52 7.11 1.63 5.94 6.15 ¦ KURT i' 18. 23.51 10.20 3.60 2.42 0.90 2.43 2.16 2.34 2.29 1.30 4.30 3.00 2.57 2.44 SKEW DEV 667.47 343.48 189.90 53.45 23.45 55.16 40.83 70.35 113.48 60.33 8.94 1050.89 STD 607.18 1055.78 534.76 258.78 49.22 23.25 51.49 45.69 28.84 56.00 27.58 5.45 MEAN 123 1 ))) Group Group Group Group Group Group 3 CHARACTERISTICS 2 3 (cont.'d) CALANOIDS 31s/m Station Station Station 3 CLADOCERA Station Station Station ivIdua 1975 1976 1977 LIVING TOTAL (Ind LARVACEA (individuals/m TOTAL (individuals/m PELAGIC ZOOPLANKTON 84 85 N 124 119 121 123 75.12 3.10 9.91 436.59 101.69 100.00 CX EMPXR 95% 0,58 2.66 0.08 0.01 0.05 0.00 KURT 93.12 24.16 17.44 67.94 56.68 -0.68 SKEW 9.21 4.51 4.03 8.03 6.86 -0.15 5.02 5.18 DEV 422.68 753.79 14.32 26.10 STD 7.80 1.06 2.30 134.94 351.40 56.97 MEAN 7 8 ) HYDROCARBONS PHYTANE n-Ci 18 CHARACTERISTICS HYDROCARBONS 11-C32)/gram) n-Ci /n-ALKANES percent) vs. vs. to to Ph) LOW + LIVING TOTAL (n-Cm (micrograms PRISTANE PRISTANE PHYTANE (Pr (n-Cm (relative SUM 1 HIGH-MOLECULAR-WEIGHT ZOOPLANKTON (1975-1977) vs. n-C PELAGIC A-70 N 72 62 123 123 103 105 61.36 66.14 36.74 Cl 13333.3 90000.0 70.0 EMPIR -- 95% 0.00 0.00 0.69 -1,3 27.3 8200.0 KURT 1.08 1.46 % 12.10 3.68 3.24 9.90 0.85 1.37 3.35 1.99 1.47 2.68 SKEW DEV 18.67 20.94 8.41 19.99 3716.53 20582.30 STD 26.49 16.55 5.37 18.08 MEAN 2750.45 38044.09 HYDROCARBONS 32) 32) n-C n-C CHARACTERISTICS n-Catt) percent) percent) weight) weight) weight) toto to dry dry dry MID HIGH LIVING SUM (n-Ci9 (relative SUM (n-Czs (relative AVERAGE (n-Cji, IRON (ppm CALCIUM (ppm VANADIUM (ppm 'd) METALS HIGH-MOLECULAR-WEIGHT OEP ZOOPLANKTON (1976-1977) PELAGIC (cont. TRACE N 141 67 136 144 143 140 144 500.00 64.00 20.00 75.00 11.10 Cl 29000.00 6.50 EMPIR 95% 0.60 2,00 5,50 0.10 0.80 32.00 90.00 KURT 34.30 3.00 27.67 12.11 128.73 0.50 -0.62 5.48 1.90 4.61 2.85 0.98 0.26 SKEW 11.12 5.35 3.08 1.54 DEV 183.80 7319.55 19.73 95.09 STD 12.60 7.03 26.34 3.99 3.32 MEAN 157.06 5280.86 CHARACTERISTICS weight) weight) weight) weight) weight) weight) weight) (cont.'d) dry dry dry dry dry dry dry LIVING ZINC (ppm ALUMINUM (ppm LEAD (ppm NICKEL (ppm COPPER (ppm CHROMIUM (ppm CADMIUM (ppm METALS PELAGIC TRACE A-72 N 241836242424 36363642 241836 186 186 Cl 9.79 6.46 8.69 9.23 10.08 9.85 9.95 10.08 9.85 9.83 9.78 4.22 3.78 4.00 4.28 EMPIR 95% 3.69 3.44 4.38 5.40 4.97 5.01 8.98 4.55 6.63 3.69 3.44 2.47 1.38 3.14 2.94 KURT -0.47 -1.05 -1.55 -0.48 -0.17 -0.68 -0.74 -1.08 -1.27 1.18 -0.98 1.69 1.05 1.02 0.42 0.27 0.04 0.54 1.26 1.04 SKEW -0.75 -0.49 -0.25 -1.02 -0.82 -0.20 -0.23 -1.62 -0.04 -1.01 DEV 1.72 0.96 1.63 1.07 1.44 1.56 0.26 1.59 0.94 1.87 2.00 0.43 0.61 0.24 0.33 STD 7,70 4.85 6.79 7,65 8.12 8.20 9.47 7.50 8.32 8.23 6.37 3.26 3.09 3.44 3.49 MEAN 12 3456 123 SIZE II III IV GRAIN Group Group Group Group Group Group CHARACTERISTICS SIZE Group Group DEVIATION Group I MEAN GRAIN Station Station Station Station Station Station Transect Transect Transect Transect units) Station Station Station units) STANDARD (0 NON-LIVING TEXTURE SEDIMENT SEDIMENT SEDIMENT (1976-1977) (0 BENTHIC N Cl 4.34 4.38 3.21 3.78 3.59 3.40 4.34 9.3 81.78 87.3 74.2 55.3 61.6 60.9 74.4 30.6 87.3 81.8 EMPIR ----— - 95% 2.61 2.71 2.58 2.61 2.71 1.38 2.58 1.03 4.5 2.5 2.2 1.0 0.4 2.2 1.0 0.9 0.4 39.7 6.33 0.05 1.6 KURT -0.50 -0.60 -0.88 -0.05 -0.68 -1.47 -1.1 -1.5 -0.3 -0.3 -0.1 -0.6 -0.9 -0.6 -1.1 0.80 0.72 0.04 -0.59 -0.68 -2.03 -0.27 1.17 0.7 0.8 1.2 1.2 0.7 0.7 0.5 1.8 SKEW -0.5 -0.5 0.49 0.49 0.17 0.28 0.25 0.39 0.58 2.5 DEV 24.44 14.9 26.5 14.6 20.6 20.9 21.8 8.0 28.8 26.8 STD 3.37 3.28 2.89 3.34 3.22 2.93 3.54 3.5 MEAN 22.86 67.1 32.3 20.5 18.1 17.4 27.2 11.5 17.0 44.3 6 16 45 2345 CHARACTERISTICS III III IV III III IV Group Group Group Group Group Group Group Group Group (cont.’d) Station Station Station Transect Transect Transect Transect SAND Station Station Station Station Station Station Transect Transect Transect Transect NON-LIVING TEXTURE PERCENT BENTHIC SEDIMENT N 241836242424 36363642 2418362424 186 186 Cl 47.55 27.8 49.0 48.8 43.1 40.2 33.7 41.8 49.0 44.3 31.4 71.61 32.9 55.1 62.8 74.8 72.2 EMPIR -------—--­ -—---­ 95% 8.64 6.9 9.6 8.7 8.6 6.9 14.6 11.9 13.3 26.3 26.3 8.87 2.9 15.3 30.1 26.5 25.8 KURT -0.54 -0.8 -1.6 -0.4 -1.2 -0.3 -0.0 -0.5 -0.7 0.5 -1.3 -0.69 -1.2 -1.4 -1.1 -1.2 -1.4 SKEW -0.58 0.7 -0.6 -0.4 -0.6 -1.0 0.6 -0.5 0.3 -1.2 0.3 -0.44 0.1 -0.3 0.5 -0.6 -0.4 DEV 6.9 8.7 8.7 1.8 8.6 6.2 8.0 8.8 10.66 14.3 10.2 10.5 17.42 13.6 10.6 10.2 15.0 STD 30.37 14.7 30.7 34.4 29.8 29.9 29.6 28.7 37.1 31.5 18.6 46.77 18.2 37.5 45.1 52.1 52.6 MEAN 123456 123 5 4 CHARACTERISTICS I II III IV Group Group Group Group Group Group Group Group Group Group Group (cont.'d) SILT CLAY Station Station Station Station Station Station Transect Transect Transect Transect Station Station Station Station Station NON-LIVING TEXTURE PERCENT PERCENT BENTHIC SEDIMENT 24 36363642 75 1291812 1212 75 N 1.32 1.04 0.85 1.19 1.25 1.32 1.62 73.3 74.8 72.2 70.3 71.6 -18.90) Cl EMPXR (• - 95% -2.9 9.8 -0.08 0.300.50 0.540.56 -0.10-0.55 60.3 16.4 32.3 (-20.60)­ 0.08 2.75 0.49 KURT -0.5 -1.2 -1.3 0.8 -0.9 -1.57 -0.19 -0.30 -0.67 -0.98 SKEW -0.3 0.2 0.1 -1.5 0.6 -0.43 0.12 -0.72 -0.51 -0.38 0.14 -1.05 0.82 3.3 0.32 0.34 0.18 0.18 0.22 0.25 0.26 0.45 DEV 17.0 12.1 20.5 19.3 STD 0.85 0.48 0.62 0.88 0.94 0.93 1.17 67.0 44.2 51.4 51.5 37.1 -19.95 MEAN the CARBON weight from 6 123456 ORGANIC 13 IIIII IV C CHARACTERISTICS (cont.'d) Group carbon/dry Group Group Group Group Group Group deviations I TOTAL DELTA Station Transect Transect Transect Transect organic sediment) Station Station Station Station Station Station standard) mil NON-LIVING TEXTURE CHEMISTRY SEDIMENT (% SEDIMENT (per PDB BENTHIC SEDIMENT SEDIMENT (1977) N 12918 121212 252525 18 181821 85 Cl (-18.44) (-19.19) (-19.50) (-19.73) (-19.52) (-19.93) (-19.20) (-18.90) (-18.44) (-19.15) (-19.19) (-18.44) (-18.90) 1.45 EMPIR - 95% 0.04 (-19.93)-(-20,40)-(-20,42)-(t-20,58)-(-20.55)-(-20.70)-(-20.60)-(-20.58)-(-20.70)-(-20.58)-(-20.70)-(-20.40)-(-20.50)­ KURT -0.21 0.10 -1.43 -0.82 -1.09 -0.27 1.18 -0.01 1.02 -1.13 0.20 4.37 -0.58 4.37 SKEW 0.28 -0.74 0.26 0.17 0.53 -0.43 1.02 0.87 0.48 0.48 0.95 1.86 0.65 1.72 DEV 0.46 0.37 0.31 0.26 0.36 0.22 0.33 0.46 0.48 0.46 0.41 0.45 0.44 0.38 STD : MEAN -19.34 -19.69 -19.99 -20.19 -20,11 -20.29 -20.12 -20.01 -19.73 -19.99 -20.16 -19.82 -19.85 0.49 123 56 4 HYDROCARBONS CHARACTERSITICS (cont.'d) I II III IV Group Group Group Group Group Group n-Caa) HYDROCARBONS to Station Station Station Station Station Station Winter Spring Transect Transect Transect Transect NON-LIVING CHEMISTRY Fall TOTAL (n-Cji, (micrograms/gram) HIGH-MOLECULAR-WEIGHT SEDIMENT (1975-1977) BENTHIC SEDIMENT N 68 73 68 73 353537 3473 119 119 CX 8.62 1.50 0.77 0.06 29.62 21.15 35.85 54.86 57.10 66.92 47.14 EMPIR 95% 0.15 0.18 0.04 0.00 0.00 0.00 0.00 0.00 6.72 15.69 7.55 KURT 6.87 5.41 3.32 0.86 6.54 1.58 1.01 10.63 0.67 -0.43 2.44 2.34 2.06 1.48 1.02 1.77 1.28 0.78 2.64 1.05 0.52 1.40 SKEW 2.08 0.32 0.21 0.01 8.34 5.26 7.93 9.30 9.76 DEV 12.97 12.90 STD MEAN 2.55 0.55 0.31 0.02 9.78 4.76 11.86 13.22 23.79 35.39 20.32 17 18 PHYTANE n-C n-C CHARACTERISTICS (cont.'d) Ph)/n-ALKANES n-Cjs) percent) n-C2i*) percent) vs. vs. to to vs. Winter Spring Fall 1975 1976 + LOW MID NON-LIVING CHEMISTRY PRISTANE PRISTANE PHYTANE (n-Cjit (relative (n-Cig (relative (Pr SUM SUM BENTHIC SEDIMENT N 119 34 73 Cl 90.82 83.30 90.82 EMPIR 95% 20.15 19.91 20.15 KURT 0.65 -0.42 3.76 SKEW -0.75 -0.10 -1.13 DEV 14.96 15.67 11.66 STD MEAN 66.43 55.36 69.32 CHARACTERISTICS (cont.’d) 11-C32)percent) to 1975 1976 HIGH NON-LIVING CHEMISTRY (11-C25 (relative SUM BENTHIC SEDIMENT N 18 18 36 121212 36 12 1212 186 Cl 440.44 281.24 1310000.0 758400.0 632000.0 9100.0 13000.0 110000.0 8.5 EMPIR - 95% 80.0 2.0 34.56 33.20 130.0 1300.0 402000.0 115000.0 46300.0 KURT 7.49 4.33 -0.26 0.43 -0.54 0.14 15.17 0.33 3.64 3.41 0.53 2.68 2.01 0.51 0.32 1.17 3.84 1.15 1.92 2.05 0.74 SKEW -0.06 STD 408.10 249.39 21808.65 2971.58 3830.13 34379.76 1.67 DEV 322844.14 257882.45 194982.73 211454.58 MEAN 4.65 237.50 157.22 9725.83 2665.83 3070.00 477986.11 788083.33 430083.33 215791.67 23441.67 ) 2 cm SPECIES DEGRADERS DEGRADERS species/10 123 CHARACTERISTICS OIL OIL of COUNTS BACTERIA Station Station Station Winter Spring Fall MEIOFAUNA LIVING FUNGAL FUNGAL TOTAL BACTERIA TOTAL (number BENTHIC MICROBIOLOGY (1977) MEIOFAUNA (1976-1977) N 241836242424 241836242424 3636 3642 186 Cl 9.5 7.0 7.5 7.3 6.8 10.5 1153.3 1447.0 1682.5 1118.0 339.3 139.5 112.7 1118.0 283.8 1447.0 1213.0 EMPXR 95% -------­ 3.5 2.5 2.5 2.0 2.0 1.5 8.8--8.5 8.8 8.5 -8.8 77.819.523.5 11.5 12.514.3 KURT -0.03 0.21 1.61 1.26 -0.56 -0.42 6.09 -1.1 4.3 19.2 3.2 -0.4 0.7 3.3 4.4 3.1 2.0 0.2 0.6 1.1 0.8 0.4 0.4 2.50 0.2 1.9 4.0 1.8 0.8 1.0 1.9 2.1 2.1 1.6 SKEW DEV 1.7 1.8 1.1 1.2 1.4 1.3 311.04 408.7 432.7 193.6 81.4 38.9 26.7 264.5 10.2 412.6 402.6 STD 6.7 5.5 4.4 4.1 4.2 4.0 MEAN 202.86 710.3 347.5 140.5 91.0 60.7 42.0 211.1 69.0 248.8 336.9 ) 2 cm 10 123456 123456 DENSITY individuals/ CHARACTERISTICS *d) of Transect Transect Transect Transect StationGroup StationGroup StationGroup StationGroup StationGroup StationGroup MEIOFAUNA StationGroup StationGroup StationGroup StationGroup StationGroup StationGroup I II III IV (cont. LIVING TOTAL (number BENTHIC MEIOFAUNA N 241836242424 36363642 24 18362424 186 186 238.0 109.5 75.5 226.0 992.5 56.0 130.0 49.5 23.3 24.5 11.8 Cl 903.5 1267.5 1313.5 580.5 731.0 1267.5 EMPIR - 95%--------­ 4.5 -7.88.0 8.3 3.3 4.5 3.3 4.5 6.5 8.5 0.0 0.0 0.0 0.0 0.0 0.0 26.5 KURT 6.70 -0.8 3.6 11.3 2.7 -0.5 0.4 1.2 9.7 3.8 1.5 29.75 5.5 10.6 12.5 16.1 10.7 2.60 0.1 1.8 3.1 1.6 0.8 1.1 1.5 2.7 2.2 1.5 4.92 2.1 3.0 3.5 3.9 2.9 SKEW 4.8 5.1 2.5 DEV 246.83 338.1 348.4 109.8 55.8 32.2 19.6 200.5 41.4 329.7 331.1 15.26 30.3 11.4 STD 6.35 8.3 2.7 2.5 1.9 MEAN 152.17 268.5 91.4 66.9 46.4 26.7 158.6 45.5 189.1 267.1 24.5 578.6 )) 22 cm cm 10 6 12 45 12345 3 individuals/ DENSITY individuals/10 Group Group Group Group Group Group II III IV Group Group Group Group Group CHARACTERISTICS DENSITY I of of Station Station Station Station Station Station Transect Transect Transect Transect ID Station Station Station Station Station ACT (cont.'d) ICO LIVING NEMATODE (number HARP (number BENTHIC MEIOFAUNA A-82 N 24 36363642 241836242424 363636 186 Cl 6.0 7.5 36.3 130.0 49.5 201.0 226.0 161.0 115.0 169.0 133.0 91.0 156.0 107.0 207.0 EMPIR ----_ 95% 0,0 0.0 0.0 0.0 0.0 26.0 38.0 32.0 26.0 20.0 29.0 14.0 34.0 27.0 20.0 0.8 1.6 9.3 2.63 -0.81 0.53 1.21 -0.87 1.11 1.58 1.24 2.62 KURT 11.2 12.9 -1.51 SKEW 1.4 3.2 1.3 3.4 2.9 1.72 -0.01 0.98 0.81 1.30 0.39 -0.27 1.02 1.20 1.96 1,8 7.3 1.8 DEV 25.7 13.7 41.82 61.6 46.9 20.2 39.5 31.7 17.4 26.3 18.7 50.3 STD MEAN 1.5 4.2 1.9 11.8 7.9 70.63 129.9 73.5 56.6 68.6 76.5 57.1 73.4 51.2 67.6 ) 2 m 6 123456 I II Group III IV Group Group Group Group Group Group I II III species/0.1 CHARACTERISTICS SPECIES Station Transect Transect Transect Transect Station Station Station Station Station Station Transect Transect Transect (cont.'d) LIVING INFAUNA (number MEIOFAUNA MACROINVERTEBRATES (1976-1977) of BENTHIC N 42 241836242424 36363642 186 185 185 Cl 206.0 4475.0 6770.0 2249.0 1877.0 1063.0 639.0 324.0 4303.0 884.0 6772.0 3084.0 19.0 823.0 EMPIR 1.0 2.0 95% 14.0 47.0 62.0 43.0 58.0 37.0 69.0 37.0 50.0 37.0 491.0 323.0 5.46 0.27 4.61 2.09 3.35 1.31 2.38 KURT -0.56 12.40 -0.36 -0.12 10.34 -0.77 18.97 0.48 3.36 0.64 1.08 2.75 2.37 0.48 0.18 2.14 1.22 2.17 1.49 0.99 3.78 SKEW DEV 4.43 52.5 1077.35 1834.9 582.1 332.8 259.8 160.9 71.2 959.2 181.3 1886.6 952.5 218.06 STD MEAN 105.1 667.53 2726.3 922.3 404.9 255.0 290.8 167.3 801.5 281.4 1043.4 885.2 8.58 136.34 ) 2 0.1 m /trawl)/trawl) 1 234 56 IV Group Group Group II III IV (cont.'d) individuals/ Group Group Group species individuals CHARACTERISTICS I SPECIES DENSITY DENSITY ES of ofof Transect Station Station Station Station Station Station Transect Transect Transect Transect LIVING ERTEBRAT INFAUNA (number EPIFAUNA (number EPIFAUNA (number BENTHIC MACR.Q1NV 9 N 46 185 185 185 CX 1.77 98.56 27.0 566.0 8142.7 EMPIR - 95% 4.0 8.0 0.0 1.74 175.1 KURT 0.22 24.11 18.10 25.95 0.20 0.52 4.20 3.18 4.70 0.95 SKEW DEV 5.64 0.28 STD 167.82 2630.03 31.76 MEAN 14.30 126.69 2708.76 0.15 36.79 /trawl)trawl) HYDROCARBONS gonad species/ individuals n-Caz) CHARACTERISTICS HYDROCARBONS n-Cs2)oampechanus-HYDROCARBONS of of to to SPECIES DENSITY BIOMASS tecus (grams/trawl) (micrograms/gram) (micrograms/gram) as LIVING FISHES FISH (number FISH (number FISH TOTAL (n-Ci«+ TOTAL (n-CmPenaeus BENTHIC DEMERSAL (1976-1977) HIGH-MOLECULAR-WEIGHT (1975-1977) Lutjanus A-85 9 11 20 20 119 145 N Cl 20,01 43,80 24,10 4.80 24.10 15.83 15.83 3.31 EMPIR 0.00 1.13 0.00 0.00 6.00 1.13 1.13 95% 12.81 KURT 3.72 9.88 0.12 4.79 -1.09 -1.70 -0.35 -1.62 1.87 2.90 1.09 2.10 0.59 0.67 0.69 SKEW -1.04 DEV 6.06 9.55 7.77 1.48 6.51 6.35 1.25 0.87 STD 4.67 8.68 6.58 0.90 6.59 2.09 13.51 14.70 MEAN gill HYDROCARBONS 11-C32)11-C32)ITL-C2I+) percent) n-Cs2) CHARACTERISTICS oampeohanus-HYDROCARBONS oampeohanus-llver HYDROCARBONS to totO to 1976 1977 1976 1977 MID LIVING TOTAL (n-Cm (micrograins/gram) TOTAL (n-Cut (mlcrograms/gram) (n-Cig (relative AVERAGE (n-Cm *d) Lutjanus SUM HIGH-MOLECULAR-WEIGHT Lutjanus OEP BENTHIC (cont. N 21 109 20 18 Cl 7,40 30,62 25.31 4.38 35,85 EMPIR -­ - 95% 0.0 0.0 2,32 0.02 0.57 KURT 18.43 4.68 6.89 0.59 0.08 4.19 2.10 2.56 1.17 0.84 SKEW DEV 1.58 9.41 7.24 1.30 9.78 STD 0.68 6.95 6.85 1.37 MEAN 13.60 gill -gonad muscle -liver HYDROCARBONS -muscle )32 32) gram) CHARACTERISTICS 11-C32)aurorubens-aurorubens 11-C32)aurorubens-11-C32)aurorubens n-C n-C campeohanus HYDROCARBONS HYDROCARBONS HYDROCARBONS HYDROCARBONS HYDROCARBONS to to to toto (micrograms/gram) (micrograms/gram) (micrograms/gram) (micrograms/gram) (micrograms/ ltf 11* LIVING TOTAL (n-Cm TOTAL (n-C TOTAL (n-Cm TOTAL (n-Cm TOTAL (n-C d) HIGH-MOLECULAR-WEIGHT Lutjanus Rhomboplites Rhomboplites Rhomboplites Rhomboplites f BENTHIC (cont. 1113322 11 15 2526 N Cl 36,00 7.03 6.31 36.00 26.08 7.07 6.94 10.34 2.18 1.85 51.32 8.58 EMPIR 95% 1,85 7.03 6.31 36.00-12.55-4.27-3.646.59 2.181.85-0.03 0.02 2.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.60 11.70 KURT SKEW 1.65 0.00 0.00 0.00 -1.42 -0.68 0.00 0.00 0.00 0.00 2.47 3.32 DEV 9.92 0.00 0.00 0.00 7.22 1.41 2.33 2.65 0.00 0.00 12.00 1.85 STD 7.03 6.31 5.78 5.29 8.46 2.18 1.85 8.58 1.05 10.67 36.00 20.60 MEAN HYDROCARBONS )) 11-C17 32 32 gram) n-C n-C CHARACTERISTICS lathami HYDROCARBONS caprinus HYDROCARBONS to to Winter March April Spring July August Fall November December (micrograms/gram) (raicrograms/ LIVING PRISTANE TOTAL (n-Cm TOTAL (n-Cm *d) Traohurus Stenotomus HIGH-MOLECULAR-WEIGHT vs. BENTHIC (cont. A-88 N 442637 51 CX 0.68 14.09 15.80 68.00 EMPIR - 95% 0,00 0.00 0.12 20.00 KURT 6.30 -0.47 3.27 2.73 2.58 0.88 2.01 SKEW -0.83 DEV 3.35 0.21 4.33 8.79 STD 1.93 0.19 3.04 MEAN 52.90 HYDROCARBONS n-Caa)aquilonavis 3 flesh CHCARACTERISTICS HYDROCARBONS 11-C32)atrobranohus HYDROCARBONS HYDROCARBONS weight) to toto azteous­ (micrograms/gram) (micrograms/gram) 2)(micrograms/gram) pealei dry LIVING TOTAL (n-Cm TOTAL (n-Cm TOTAL (n-Cm ZINC (ppm METALS d) * Serranus Penaeus HIGH-MOLECULAR-WEIGHT Loligo Pristipornoides n-C BURDENS (1975-1977) BENTHIC (cont. TRACE BODY N51 2416 16 24 17 Cl 0.25 0.30 50.00 17.00 0,16 2500.00 EMPIR -­ - 95% 0.01 0.01 10.00 2,00 0.02 310.00 0.36 0.33 7.61 0.84 1.46 -0.82 KURT 0.83 1.20 2.37 1.11 0.45 SKEW -0.72 0.08 0.09 3.28 0.05 DEV 11.20 498.97 STD MEAN 0.11 0.09 22.75 10.88 0.08 882.5 lesh flesh-flesh CHARACTERISTICS (cont.'d) weight) lathami weight) weight) weight) atrobranohus-f weight) oaprinus-weight) dry dry dry dry dry dry LIVING CADMIUM (ppm CADMIUM (ppm CALCIUM (ppm ALUMINUM (ppm ZINC (ppm CADMIUM (ppm METALS Traohurus Serranus Stenotomus BENTHIC TRACE A-90 5 N Cl 0,70 EMPIR - 95% 0.15 KURT -3.10 SKEW 0.55 DEV 0.26 STD MEAN 0.39 BENTHIC LIVING CHARACTERISTICS TRACE METALS (cont.M) Lutjanus oampechanus -gill VANADIUM (ppm dry weight) APPENDIX B VARIABLE GEOGRAPHIC DISTRIBUTIONAL MAPS B-2 PREFACE The purpose of this appendix is to present a quick reference to the distributional characteristics of those environmental variables measured during the south Texas outer continental shelf (STOCS) study that showed significant (P < 0.05) spatial variation over the study area. Presented are the mean and 95% normal confidence interval statistics for every station on the Texas shelf sampled over the study period (1975-1977). The intention of this presentation is to provide decision-makers and environ­ mental managers with a quick reference to the study area in respect to those variables included, so that he/she can make a decision concerning the management of the ecosystem or develop criteria for further monitoring of the system. Sampling Scheme The variables presented represent several different sampling schemes. For some variables, data were collected for all three of the study years (1975-1977). Others collected data in only one or two years of study. For further reference concerning extent of sampling, the reader should see the specific scientific section concerning a certain variable in Volume 111. The means and confidence intervals presented in the distributional maps of this appendix represent data collected during the three meteorolo­ gical seasons of each year only; winter, spring and fall. Spatially, two different sampling schemes are presented in the maps: a) a 12 station scheme involving Stations 1-3, Transects I-IV, primarily for pelagic sampling (Figure B-l); and b) a 25 station scheme involving Stations 1-6, Transects and Stations 1-7, Transect IV, primarily for the LORAN and LORAC benthic sampling (Figure B-l), Table B-l lists coordinates, as well as latitude, longitude and water depth of each site one of the two schemes described above. represented by sampling B-4 Figure B-l. Map showing the south Texas outer continental shelf bathymetry and location of sampling sites. TABLE B-l BLM STOCS MONITORING STUDY STATION LOCATIONS TRAN. STA. LOSAN LORAC LATITUDE LONGITUDE DEPTH 3H3 3H2 LG LR METERS FEET I 1 2575 4003 1180.07 171.46 28*12’N 96*27’W 18 59 2 2440 3950 961.49 275.71 27*55'N 96*20'W 42 138 3 2300 3863 799.45 466.07 27*34’N 96*07’W 134 439 4 2583 4015 1206.53 157.92 28*14'N 96*29'W 10 33 5 2360 3910 861.09 369.08 27"44'N 96*14’W 82 269 6 2330 3892 819.72 412.96 27*39’N 96*12’W 100 328 II 1 2078 3962 373.62 192,04 27*40fN 96*59'W 22 72 2 2050 3918 454.46 382.00 27*30'N 96*45'W 49 161 3 2040 3850 564.67 585.52 27*18’N 96*23’W 131 430 4 2058 3936 431.26 310.30 27*34'N 96*50’W 36 112 5 2032 3992 498.85 487.62 27*24'N 96*36’W 78 256 6 2068 3878 560.54 506.34 27*24'N 96*29'W 98 322 7 2045 3835 27*15’N 96*18,5’W 182 600 III I 1585 3880 139.13 909.98 26*58'N 97*11’W 25 82 2 1683 3841 286.38 855.91 26*58'N 96*48’W 65 213 3 1775 3812 391.06 829.02 26*58'N 96*33’W 106 348 4 1552 3885 95.64 928.13 26*58'N 97*20’W 15 49 5 1623 3867 192.19 888.06 26*58'N 97*02’W 40 131 6 1790 3808 411.48 824.57 26*58’N 96*30’W 125 410 1 1130 3747 187.50 1423.50 26*10’N 97*01'W 27 88 2 1300 3700 271.99 1310.61 26"10’N 96*39’W 47 154 3 1425 3663 333.77 1241.34 26*10'N 96*24'W 91 298 4 1073 3763 163.42 1456.90 26*10’N 97*08'W 15 49 5 1170 3738 213.13 1387.45 26*10'N 96*54’W 37 121 6 1355 3685 304.76 1272.48 26*10'N 96*31’W 65 213 7 1448 3659 350.37 1224.51 26*10'N 96*20'W 130 426 IV HR 1 2159 3900 635.06 422.83 27*32’05" 96*28’19" 75 246 2 2169 3902 644.54 416.95 27*32’46" 96*27*25" 72 237 3 2163 3900 641.60 425.10 27*32’05" 96*27’35" 81 266 4 2165 3905 638.40 411.18 27*33’02" 96*29’03" 76 250 SB 1 2086 3889 563.00 468.28 27*26’49" 96*31’18" 81 266 2 2081 3889 560.95 475.80 27*26’14" 96*31’02" 82 269 3 2074 3890 552.92 475.15 27*26’06" 96*31’47" 82 269 4 2078 3890 551.12 472.73 27*26’14" 96*32’07" 82 269 B-6 INDEX TO VARIABLE DISTRIBUTIONAL MAPS Page Surface Water Silicate B-7 Surface Net Chlorophyll B-8 B-9 Surface Net Phaeophytin B-10 Bottom Water Phosphate Bottom Water Dissolved Oxygen B-ll B-12 Bottom Water Total Chlorphyll B-13 Bottom Water Propene Bottom Water Ethene B-14 Copepod Total Density B-15 Sediment Mean Grain Size B-16 Sediment Grain Size STD B-17 Sediment Total Organic Carbon B-18 13 B-19Sediment Delta C B-20Total Sediment Bacteria B-21 Total Meiofauna Species Total Meiofauna Density B-22 Nematode Density B-23 Harpacticoid Density B-24 Infauna Species B-25 Infauna Density B-26 SURFACE WATER SILICATE B-8 SURFACE NET CHLOROPHYLL SURFACE NET PHAEOPHYTIN B-10 BOTTOM WATER PHOSPHATE BOTTOM WATER DISSOLVED OXYGEN 8-12 BOTTOM WATER TOTAL CHLOROPHYLL BOTTOM WATER PROPENE B-14 BOTTOM WATER ETHENE COPEPOD TOTAL DENSITY B-16 SEDIMENT MEAN GRAIN SIZE SEDIMENT GRAIN SIZE STD B-18 SEDIMENT TOTAL ORGANIC CARBON SEDIMENT DELTA Cl3 B-20 TOTAL SEDIMENT BACTERIA TOTAL MEIOFAUNA SPECIES B-22 TOTAL MEIOFAUNA DENSITY B-23 NEMATODE DENSITY B-24 HARPACTICOID DENSITY B-25 INFAUNA SPECIES B-26 INFAUNA DENSITY