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Rates of marsh wetland loss in the northern Gulf of Mexico are the highest observed in North America. Marsh terraces have been implemented over the last 30 years to address this loss. Marsh Terraces reduce fetch and resulting wave energy which, reduces rates erosion of sediments in coastal wetlands. This thesis evaluated marsh terraces by extensive data collection that will assess the spatiotemporal relationships between wind patterns, wave parameters, and sediment strength in water bodies modified with marsh terraces. Data collected during two four-month deployments captured the passage of 40 cold front storms and the passage of Hurricane Barry. Results indicated that the mean threshold for erosion for marsh platform and terraces (0.194 N/m2 and 0.500 N/m2) were often exceeded during the passage of cold front storms. Orientation to reduce the influence of these storms was determined to be 270/55 which is perpendicular to cold front associated winds.

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Mass transport deposits form a significant portion of the rock record in both modern and ancient basins. Their geometry, composition, distribution and genesis are poorly understood, making it difficult to predict anything about these deposits in assessing subsurface basin stratigraphy or modern seafloor hazards. A tremendous effort has been made in the last few years to characterize and better understand seafloor failures in numerous margins of the world. These mass failures have triggered the interests of geologists, particularly in the oil and gas industry, as they can form prominent seals and reservoirs. To increase our knowledge base of mass transport complexes (MTCs), the characteristics of 259 siliciclastic deposits worldwide, were analyzed in terms of their volume, area, length, thickness, lithology, and tectonic settings. In some instances, MTCs were geo-referenced and digitized into ArcGIS and their dimensions were calculated. These data reveal several interesting points and suggest a number of statistically significant predictive relationships. Sand-rich mass transport deposits show a propensity to be short and thick. Muddy MTCs show a propensity to be longer and thinner. The highest number and largest volume of clastic mass transport deposits occur along passive margins. These mega-MTCs are typically muddy with lengths up to 800 km and volumes up to 5000 km3. Sandy and gravelly Quaternary-age MTCs show maximum lengths of less than 300 km and with volumes less than 2000 km3. Pre-Quaternary MTCs are systematically under-documented in literature, but known occurrences are found in passive, active and convergent margins. The largest (30,000 to 40,000 sq km) occur along the older Tertiary margin of West Africa. To date, 41 separate mass transport deposits composed dominantly of carbonate material have been identified in literature. The most extensive and voluminous (7000 km3) carbonate mass transport complexes occur in the Citronens Fjord, Offshore Greenland. They are 200m thick, Silurian-age mega-breccias that were deposited in a convergent margin setting. On comparison carbonate MTCs tend to show longer flows with coarser grain sizes, while clastics show coarser grained deposits to be of more limited length. The Mad Dog area, Gulf of Mexico is a region of active salt tectonics and mass transport processes. Consequently, it was selected to form a focus study area to test the relationships developed during this project. MTCs in this region were grouped into four main types based on their size, geomorphology and internal structure. Their geometries indicate they are comparable to MTCs found offshore Oregon and New Jersey and are most likely muddy in nature. / text

Hurricanes can temporarily disrupt seasonal patterns of fish assemblage change or result in permanent changes in fish assemblages. I studied the effects of two hurricanes on fish assemblages at the Chandeleur Islands and the possible influence that storm-generated tidal channels may have on the composition of local fish assemblages. I also compared recently collected data to historic ichthyofaunal survey data collected over thirty years ago at the Chandeleur Islands. Near shore fish assemblages changed the most after hurricanes but changes in species composition were primarily due to increases in abundance and diversity. During July 2007 there was no significant difference between fish assemblages in channel and seagrass habitats, although significant differences among wash-over channels existed. Loss of habitat and the increased intensity and frequency of recent storms may explain why current fish assemblages at the Chandeleur Islands are less diverse (as measured by taxonomic distinctness) than assemblages collected during 1969-1971.

Time-lapse seismic allows oil/gas reservoir monitoring during production, highlighting compaction and water movement. Time-lapse modeling, using a stress-dependent rock physics model, helps determine the need and frequency of expensive repeat seismic acquisition. We simulate a Gulf of Mexico gas reservoir time-lapse response for depletion and water flooding using uncertainty ranges in water saturation, porosity, stress-induced velocity changes, and pore compressibility. An analysis is conducted to see if a water-swept region could have been predicted. Findings show the swept and un-swept monitor cases amplitude differences range from 6% to 15%, which is higher than the actual monitor seismic noise level. Thus, it is unlikely these cases could be differentiated. However, the modeled amplitude changes from base to monitor cases do not match measured amplitude changes. This suggests the rock property model requires pressure-variance improvement and/or the changes in seismic amplitudes are associated with pressure/porosity, thickness, or saturation cases not modeled.

A 1-D tidal, salinity and water quality model that analyzes the impacts of freshwater diversions with median and high flow on the water level, salinity and nutrient concentration of the Barataria Basin over a 2 period is presented here. The model predicts that the salinity of Lower Barataria decreases with the introduction of freshwater diversions. The model also predicts that nutrient concentration increases in Barataria Basin and decreases in Northern Gulf of Mexico with the introduction of diversions. The model shows the impact of freshwater diversions on water level except in the neighborhood of the diversion sites are small.

The western portion of the Mississippi/Atwater fold belt in the Gulf of Mexico contains what is known as The Green Knoll Salt Dome. The creation and growth of this salt diapir is punctuated by salt deposition, salt migration, sediment loading, and is linked to the “Frampton” fold belt. An indicator of these growth periods is exhibited in an angular unconformity (halo-kinetic sequence boundary) that flanks the diapir. This unconformity developed during the Miocene-Pliocene chronostratigraphic boundary. The “Redwood” (Green Canyon 1001) prospect was drilled after the discovery of middle Miocene sands containing hydrocarbons in the Mad Dog field (GC 826). The objective Miocene sand in the “Redwood” borehole was thin due to this angular unconformity causing the sand to pinch out. An evaluation of seismic and well log data provided by Bureau of Ocean Energy Management indicated that the unconformity might not provide the seal needed to trap hydrocarbons on the flank of the salt dome, or it did not allow enough sand to be deposited. A palinspastic structural restoration of the Green Knoll Salt Dome revealed that the growth of the Green Knoll and Frampton are connected. It is still possible that if a well were to be drilled further down dip from where The “Redwood” prospect was drilled, one may find a potential hydrocarbon reservoir.

In the event of a natural or anthropogenic disturbance, environmental resource managers require a reliable tool to quickly assess the spatial extent of potential damage to the seagrass resource. The temporal availability of the Landsat 5 Thematic Mapper (TM) imagery, 16-20 days, provides a suitable option to detect and assess damage to the seagrass resource. In this study, remote sensing Landsat 5 TM imagery is used to map the spatial extent of the seagrass resource. Various classification techniques are applied to delineate the seagrass beds in Clearwater Harbor and St. Joseph Sound, FL. This study aims to determine the most appropriate seagrass habitat mapping technique by evaluating the accuracy and validity of the resultant classification maps. Field survey data and high resolution aerial photography are available to use as ground truth information. Seagrass habitat in the study area consists of seagrass species and rhizophytic algae; thus, the species assemblage is categorized as submerged aquatic vegetation (SAV). Two supervised classification techniques, Maximum Likelihood and Mahalanobis Distance, are applied to extract the thematic features from the Landsat imagery. The Mahalanobis Distance classification (MDC) method achieves the highest overall accuracy (86%) and validation accuracy (68%) for the delineation of the presence/absence of SAV. The Maximum Likelihood classification (MLC) method achieves the highest overall accuracy (74%) and validation accuracy (70%) for the delineation of the estimated coverage of SAV for the classes of continuous and patchy seagrass habitat. The soft classification techniques, linear spectral unmixing (LSU) and artificial neural network (ANN), did not produce reasonable results for this particular study. The comparison of the MDC and MLC to the current Seagrass Aerial Photointerpretation (AP) project indicates that the classification of SAV from Landsat 5 TM imagery provides a map product with similar accuracy to the AP maps. These results support the application of remote sensing thematic feature extraction methods to analyze the spatial extent of the seagrass resource. While the remote sensing thematic feature extraction methods from Landsat 5 TM imagery are deemed adequate, the use of hyperspectral imagery and better spectral libraries may improve the identification and mapping accuracy of the seagrass resource.

Understanding the processes controlling the distribution and abundance of zooplankton has been a primary concern of oceanographers and has driven the development of numerous technologies to more accurately quantify these parameters. This study investigates the potential of a new plankton imaging sensor, the shadowed image particle profiling and evaluation recorder (SIPPER), that I helped develop at the University of South Florida, to address that concern. In the first chapter, results from the SIPPER are compared against concurrently sampling plankton nets and the optical plankton counter (OPC), the most widely used optical zooplankton sampling sensor in the field. It was found that plankton nets and the SIPPER sampled robust and hard-bodied zooplankton taxa similarly while nets significantly underestimated the abundance of fragile and gelatinous taxa imaged by the SIPPER such that nets might underestimate zooplankton biomass by greater than 50%. Similarly, it was determined that the OPC misses greater than a quarter of resolvable particles due to coincident counting and that it can not distinguish between zooplankton and other abundant suspended particles such as marine snow and Trichodesmium that are difficult to quantify with traditional sampling methods. Therefore the standard method of using net samples to ground truth OPC data should be reevaluated. In the second chapter, a new automated plankton classification system was utilized to see if it was possible to use machine learning methods to classify SIPPER-imaged plankton from a diverse subtropical assemblage on the West Florida Shelf and describe their distribution during a 24 hour period. Classification accuracy for this study was similar to that of other studies in less diverse environments and similar to what could be expected by a human expert for a complex dataset. Fragile plankton taxa such as larvaceans, hydromedusae, sarcodine protoctists and Trichodesmium were found at significantly higher concentrations than previously reported in the region and thus could play more important roles in WFS plankton dynamics. Most observed plankton classes were found to be randomly distributed at the fine scale (mm-100 m) and that greatest variability within plankton abundances would be encountered vertically rather than horizontally through the water column.