The circulation of the Gulf of Mexico is controlled by presence of large mesoscale structures (10-500 km). We investigate its variability and predictability from interannual to intraseasonal time scales, and the dynamical interactions between physical circulation and biological productivity. We do so by analyzing an ensemble of numerical integrations using the Regional Ocean Modeling System and hydrographic and biogeochemistry observations collected during summer field campaigns in 2010, 2011, and 2012. First, we explore the potential relationships and linkages between Mississippi-Atchafalaya River runoff, nutrient loads, and ocean dynamics from our field data. A negative correlation between nutrient concentration and salinity was confirmed at the surface and in the upper 60m of the water column for nitrite, nitrate, phosphate and silicate. No major changes in the nutrient concentrations were found between our data and previous measurements from twenty years ago. The biological activity in the stations sampled (northern Gulf) is nitrogen limited in 79% of them and phosphorus limited in 8%. Besides the direct input of nutrients from river discharges, the distribution of nutrients in intermediate and high salinity waters in the euphotic layer is influenced by dynamical processes at the ocean mesoscales such as eddies, coastal upwelling events and Loop Current (LC) intrusions. Then, using an ensemble of four model integrations we investigate how mesoscale motions dominate the variability of the Gulf of Mexico circulation both at the surface and in deep waters on intraseasonal time scales. We focus on its predictability by exploring the impact of small variations in the initial conditions and the role of the boundary conditions in the circulation evolution. In all runs, the model provides a good representation of the mean circulation features. However, the shedding of the Loop Current Eddies (LCE) differs in each run considered, and our analysis shows that the detachment of the LCE is a stochastic process. We show that the interannual variability at the model boundaries affects the representation of the LC strength and of the Yucatan Channel transport. On the other hand, the circulation in the LATEX Shelf, TAVE Shelf, and Bay of Campeche is insensitive to the details of the model boundaries, is not affected by the LC, but depends only on the wind variability, and it is therefore predictable if the atmospheric conditions are known. On the contrary, the circulation in the central basin is affected by the LC extension and by the Rings, and dominated by mesoscale features. In most of the basin, mesoscale features are coherent in the top ~ 1000 m of the water column, and below it, but not correlated between the surface and the deep layer. Coherency throughout the whole water column is attributed to particular topographic features such as the south-west corner of the Sigsbee Deep. The chaotic behavior associated with the propagation of the LCE and the elevated mesoscale activity restricts the predictability of the system at intra-seasonal scales to the coastal areas. In consequence, assimilation of continuous in-situ measurements is necessary to insure good hindcasts and forecasts at surface and below 1000 m depth. Finally, since mesoscale activity is key to understand the horizontal and vertical dynamics in the Gulf, we further analyze the model representation of mesoscale circulation under low (monthly) and high (6 hourly) frequency atmospheric forcing. The temporal scale variation from monthly to 6-hourly in the wind forcing impacts the timing of horizontal dynamics, but not the strength. However, high frequency winds impact the model representation of vertical transport that increases as the temporal resolution of the forcing increases. Vertical velocities in the simulation forced by 6-hourly winds are ten times greater than the one obtained using monthly averaged winds. The energy injected by the winds into the ocean is transported in the water column by mesoscale eddies and near-inertial oscillations. If the forcing used by the model does not resolve the inertial frequency (1.4 days in the Gulf), then vertical transport processes are underestimated. Those processes are particularly important for the model representation of biological activity in the ocean upper layers, since they contribute to the input of nutrients into the euphotic zone.

Previous studies have come to contrasting conclusions regarding nutrient limitation of hydrocarbon biodegradation in the Gulf of Mexico, and rate measurements are needed to support oil plume modeling. Thus, this study investigates the rates and controls of biodegradation in seawater and sediments, largely in the deepsea. Sediment and seawater samples were collected on research cruises in the northern Gulf from 2012 to 2014, where the seafloor was impacted by the Deepwater Horizon (DWH) oil spill. Biodegradation was clearly limited by both nitrogen and phosphorus availability in surface waters with significant rates of CO₂ production (100 μmol CO₂ l⁻¹ d⁻¹) only observed in treatments amended with ammonium and phosphate. In deepsea sediments, nutrient amendments resulted in an average of 6 fold higher degradation rates (0.49 μmol CO₂ g sed⁻¹ d⁻¹) compared to unamended controls. Microbial communities responded to oil contamination rapidly in a series of enrichment cultures, and selection was observed for populations of native hydrocarbon-degrading bacteria. Temperature was shown to be a major factor in controlling microbial community composition in the enrichments. At room temperature, community diversity in the enrichments was significantly reduced in the presence of oil, while under 4 °C, the community diversity and evenness remained relatively high upon oil amendment. From the same deepsea sediments, 30 strains of known oil-degrading bacteria (Rhodococcus and Halomonas) were enriched and isolated with hexadecane, phenanthrene, and Macondo oil as the sole carbon and energy source. Detection of these strains in sequence libraries indicates that they may have contributed to the degradation of oil deposited onto the sediments. Rhodococccus strain PC20 degraded approximately one-third of total petroleum hydrocarbons amended into cultures within 7 days. This work elucidates the controls of biodegradation and we provide model pure cultures to further elucidate the ecophysiology of hydrocarbon degradation, focusing on deepsea sediments of the northern Gulf of Mexico.

Graduation date: 1988

Mexico is home to almost 2.9 million square kilometers of land and water surface area that is affected by water pollution and environmental degradation. While geographically more prevalent to pollution threats as well as one of the most biodiverse countries in the world, it is important to coordinate the management and regulation of coastal zones effectively to safeguard these ecosystem from degradation. However, because of the UN Convention on the Law of the Sea, nations view the problem of living resources and their management as a national priority instead of an international cooperation initiative. Mexico's fragmented, overlapping, and sometimes corrupt domestic institutions for environmental policy yield ineffective and inadequate pollution control, a result of which is a high level of marine debris presence on the coasts, as evidenced by a recent study in Veracruz, Veracruz. This marine debris, the most abundant of which is composed of plastics, is detrimental to marine life, leading to death, starvation, debilitation, reduced quality of life and lowered reproductive performance. While several avenues are being explored to mitigate marine debris in the environment, such as decreasing knowledge gaps, increasing pollution prevention measures, and education, degradation issues have compounded globally, revealing a clear picture of inadequate international regulation and convention. A stricter Mexican national regulatory system that incorporates private and public waste management organizations to incentivize and facilitate waste cleanup is needed to improve the health of the global ocean.

The discharge of sediment-laden rivers into the Mississippi Sound increases the turbidity of coastal waters. The concentration of suspended particulates is an important parameter in the analysis of coastal water quality factors. The spatiotemporal resolution associated with satellite sensors makes remote sensing an ideal tool to monitor suspended particulate concentrations. Accordingly, the presented research evaluated the validity of published algorithms that relate remote sensing reflectance (Rrs) with suspended particulate matter for the Mississippi Sound. Additionally, regression analysis was used to correlate in situ SPM concentrations with coincident observations of visible and near-infrared band reflectance collected by the MODIS Aqua sensor in order to develop a predictive model for SPM. The most robust algorithm yielded an RMSE of 15.53% (n = 86) in the determination of SPM concentrations. The application of this algorithm allows for the rapid assessment of water quality issues related to elevated SPM concentrations in the Mississippi Sound.

The forest ecosystem is a dominant landscape in the Gulf of Mexico (GOM) coastal region. Currently, many studies have been carried out to identify factors that drive forest dynamics. Changes in meteorological conditions have been considered as the main factors affecting the forest dynamics. For this study, the statistical regression analysis was used for modeling forest dynamics. Meteorological impact analysis was driven by observed data from PRISM (parameter-elevation regressions on independent slopes model) climate dataset. The forest dynamics was characterized by an indicator, the normalized difference vegetation index (NDVI). The objectives of this study are to 1) to specify and estimate statistical regression models that account for forest dynamics in the Golf of Mexico coastal region, 2) to assess which model used to capture the relationship between forest dynamics and its explanatory variables with the best explanatory power, and 3) to use the best fitted regression model to explain forest dynamics. By using fixed-effects regression methods: ordinary least squares (OLS) and geographically weighted regression (GWR), the sample-point-based regression analysis showed that meteorological factors could generally explain more than half of variation in forest dynamics. In respect of the unexplained variation of forest dynamics, the necessity of using soil to explain forest dynamics was then discussed. The result suggested that the forest dynamics could be explained by both meteorological parameters and soil texture. One of the basic considerations in this study is to include the spatiotemporal heterogeneity caused by seasonality and forest types. The model explanatory power was found differ among forest types (spatially) and seasons (temporally). By constructing regression models with randomly varying intercepts and varying slopes, the linear mixed-effects model (LMM) was fitted on composite county-based data (e.g., precipitation, temperature and NDVI). The use of LMMs was proved to be appropriate for describing forest dynamics to mixed-effects induced by meteorological changes. Based on this finding, I concluded that meteorological changes could play a significant role in forest dynamics through both fixed-effects and random-effects.

Mississippi River affects the carbon dynamics in the northern Gulf of Mexico (N-GoM) significantly. Hence, total alkalinity (TA) algorithms developed for major ocean basins produce inaccurate estimations for this region. A TA algorithm was developed, which addresses the local effects of coastal processes and complex spatial influences. In-situ data collected during numerous previous research cruises in the N-GoM were compiled and used to calculate the efficiency of an existing TA algorithm that uses Sea-Surface-Temperature (SST) and Sea-Surface-Salinity (SSS) as explanatory variables. To improve this algorithm, statistical analyses were performed to improve the coefficients and functional form of this algorithm. Then, chlorophyll-a (Chla) was included as an additional explanatory variable. Chla worked as a proxy for addressing the organic carbon pump’s pronounced effects on coastal waters. Finally, a Geographically Weighted Regression (GWR) algorithm was developed to address spatial non-stationarity, which apparently could not be addressed in the previously developed global algorithm.

No description available.

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.

No description available.