88 research outputs found
Circulation and cross-shelf transport in the Florida Big Bend
The Florida Big Bend region in the northeastern Gulf of Mexico contains both spawning sites and nursery habitats for a variety of economically valuable marine species. One species, the gag grouper (Mycteroperca microlepis), relies on the shelf circulation to distribute larvae from shelf-break spawning grounds to coastal sea-grass nurseries each spring. Therefore, identifying the dominant circulation features and physical mechanisms that contribute to cross-shelf transport during the springtime is a necessary step in understanding the variation of the abundance of this reef fish. The mean circulation features and onshore transport pathways are investigated using a numerical ocean model with very high horizontal resolution (800–900 m) over the period 2004–2010. The model simulation demonstrates that the mean springtime shelf circulation patterns are set primarily by flow during periods of southeastward or northwestward wind stress, and that significant cross-shelf flow is generated during southeastward winds. Lagrangian particle tracking experiments demonstrate that a primary pathway exists south of Apalachicola Bay by which particles are able to reach inshore, and that significantly more particles arrive inshore when they originate from an area adjacent to a known gag spawning aggregation site. The results provide, for the first time, a description of the pathways by which onshore transport is possible from gag spawning sites at the shelf break to sea-grass nurseries at the coast in the Florida Big Bend
Development of the CSOMIO Coupled Ocean-Oil-Sediment- Biology Model
The fate and dispersal of oil in the ocean is dependent upon ocean dynamics, as well as transformations resulting from the interaction with the microbial community and suspended particles. These interaction processes are parameterized in many models limiting their ability to accurately simulate the fate and dispersal of oil for subsurface oil spill events. This paper presents a coupled ocean-oil-biology-sediment modeling system developed by the Consortium for Simulation of Oil-Microbial Interactions in the Ocean (CSOMIO) project. A key objective of the CSOMIO project was to develop and evaluate a modeling framework for simulating oil in the marine environment, including its interaction with microbial food webs and sediments. The modeling system developed is based on the Coupled Ocean-Atmosphere-Wave-Sediment Transport model (COAWST). Central to CSOMIO’s coupled modeling system is an oil plume model coupled to the hydrodynamic model (Regional Ocean Modeling System, ROMS). The oil plume model is based on a Lagrangian approach that describes the oil plume dynamics including advection and diffusion of individual Lagrangian elements, each representing a cluster of oil droplets. The chemical composition of oil is described in terms of three classes of compounds: saturates, aromatics, and heavy oil (resins and asphaltenes). The oil plume model simulates the rise of oil droplets based on ambient ocean flow and density fields, as well as the density and size of the oil droplets. The oil model also includes surface evaporation and surface wind drift. A novel component of the CSOMIO model is two-way Lagrangian-Eulerian mapping of the oil characteristics. This mapping is necessary for implementing interactions between the ocean-oil module and the Eulerian sediment and biogeochemical modules. The sediment module is a modification of the Community Sediment Transport Modeling System. The module simulates formation of oil-particle aggregates in the water column. The biogeochemical module simulates microbial communities adapted to the local environment and to elevated concentrations of oil components in the water column. The sediment and biogeochemical modules both reduce water column oil components. This paper provides an overview of the CSOMIO coupled modeling system components and demonstrates the capabilities of the modeling system in the test experiments
STRATEGIC GEOGRAPHIC POSITIONING OF SEA LEVEL GAUGES TO AID IN EARLY DETECTION OF TSUNAMIS IN THE INTRA-AMERICAS SEA
The potential impact of past Caribbean tsunamis generated by earthquakes and/or massive submarine slides/slumps, as well as the tsunamigenic potential and population distribution within the Intra-Americas Sea (IAS) is examined to help define the optimal location for coastal sea level gauges intended to serve as elements of a regional tsunami warning system. The goal of this study is to identify the minimum number of sea level gauge locations to aid in tsunami detection and provide the most warning time to the largest number of people. We identified 12 initial, prioritized locations for coastal sea level gauge installation. Our study area approximately encompasses 7oN, 59oW to 36oN, 98oW. The results of this systematic approach to assess priority locations for coastal sea level gauges will assist in developing a tsunami warning system (TWS) for the IAS by the National Oceanic and Atmospheric Administration (NOAA) and the Regional Sub-Commission for the Caribbean and Adjacent Regions (IOCARIBE-GOOS)
Over what area did the oil and gas spread during the 2010 Deepwater Horizon oil spill?
Author Posting. © The Oceanography Society, 2016. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 29, no. 3 (2016): 96–107, doi:10.5670/oceanog.2016.74.The 2010 Deepwater Horizon (DWH) oil spill in the Gulf of Mexico resulted in the collection of a vast amount of situ and remotely sensed data that can be used to determine the spatiotemporal extent of the oil spill and test advances in oil spill models, verifying their utility for future operational use. This article summarizes observations of hydrocarbon dispersion collected at the surface and at depth and our current understanding of the factors that affect the dispersion, as well as our improved ability to model and predict oil and gas transport. As a direct result of studying the area where oil and gas spread during the DWH oil spill, our forecasting capabilities have been greatly enhanced. State-of-the-art oil spill models now include the ability to simulate the rise of a buoyant plume of oil from sources at the seabed to the surface. A number of efforts have focused on improving our understanding of the influences of the near-surface oceanic layer and the atmospheric boundary layer on oil spill dispersion, including the effects of waves. In the future, oil spill modeling routines will likely be included in Earth system modeling environments, which will link physical models (hydrodynamic, surface wave, and atmospheric) with marine sediment and biogeochemical components.This research was made possible by a grant from
BP/The Gulf of Mexico Research Initiative to the
CARTHE and Deep-C Consortia, and by contract
M12PC00003 from the Bureau of Ocean Energy
Management (BOEM)
Trade-Offs Between Risks of Predation and Starvation In Larvae Make the Shelf Break an Optimal Spawning Location For Atlantic Bluefin Tuna
Atlantic bluefin tuna (ABT) (Thunnus thynnus) travel long distances to spawn in oligotrophic regions of the Gulf of Mexico (GoM) which suggests these regions offer some unique benefit to offspring survival. To better understand how larval survival varies within the GoM a spatially explicit, Lagrangian, individual-based model was developed that simulates dispersal and mortality of ABT early life stages within realistic predator and prey fields during the spawning periods from 1993 to 2012. The model estimates that starvation is the largest cumulative source of mortality associated with an early critical period. However, elevated predation on older larvae is identified as the main factor limiting survival to late postflexion. As a result, first-feeding larvae have higher survival on the shelf where food is abundant, whereas older larvae have higher survival in the open ocean with fewer predators, making the shelf break an optimal spawning area. The modeling framework developed in this study explicitly simulates both physical and biological factors that impact larval survival and hence could be used to support ecosystem based management efforts for ABT under current and future climate conditions
Assessment of numerical simulations of deep circulation and variability in the Gulf of Mexico using recent observations
Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 50(4), (2020): 1045-1064, doi:10.1175/JPO-D-19-0137.1.Three simulations of the circulation in the Gulf of Mexico (the “Gulf”) using different numerical general circulation models are compared with results of recent large-scale observational campaigns conducted throughout the deep (>1500 m) Gulf. Analyses of these observations have provided new understanding of large-scale mean circulation features and variability throughout the deep Gulf. Important features include cyclonic flow along the continental slope, deep cyclonic circulation in the western Gulf, a counterrotating pair of cells under the Loop Current region, and a cyclonic cell to the south of this pair. These dominant circulation features are represented in each of the ocean model simulations, although with some obvious differences. A striking difference between all the models and the observations is that the simulated deep eddy kinetic energy under the Loop Current region is generally less than one-half of that computed from observations. A multidecadal integration of one of these numerical simulations is used to evaluate the uncertainty of estimates of velocity statistics in the deep Gulf computed from limited-length (4 years) observational or model records. This analysis shows that the main deep circulation features identified from the observational studies appear to be robust and are not substantially impacted by variability on time scales longer than the observational records. Differences in strengths and structures of the circulation features are identified, however, and quantified through standard error analysis of the statistical estimates using the model solutions.This work was supported by the Gulf Research Program of the National Academy of Sciences under Awards 2000006422 and 2000009966. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Gulf Research Program or the National Academy of Sciences. The authors acknowledge the GLORYS project for providing the ocean reanalysis data used in the ROMS simulation. GLORYS is jointly conducted by MERCATOR OCEAN, CORIOLIS, and CNRS/INSU. Installation, recovery, data acquisition, and processing of the CANEK group current-meter moorings were possible because of CICESE-PetróleosMexicanos Grant PEP-CICESE 428229851 and the dedicated work of the crew of the B/O Justo Sierra and scientists of the CANEK group. The authors thank Dr. Aljaz Maslo, CICESE, for assistance with analysis of model data. The Bureau of Ocean Energy Management (BOEM), U.S. Dept. of the Interior, provided funding for the Lagrangian Study of the Deep Circulation in the Gulf of Mexico and the Observations and Dynamics of the Loop Current study. HYCOM simulation data are available from the HYCOM data server (https://www.hycom.org/data/goml0pt04/expt-02pt2), MITgcm data are available from the ECCO data server (http://ecco.ucsd.edu/gom_results2.html), and the ROMS simulation data are available from GRIIDC (NA.x837.000:0001)
Potential Associations between Severity of Infection and the Presence of Virulence-Associated Genes in Clinical Strains of Staphylococcus aureus
BACKGROUND: The clinical spectrum of Staphylococcus aureus infection ranges from asymptomatic nasal carriage to osteomyelitis, infective endocarditis (IE) and death. In this study, we evaluate potential association between the presence of specific genes in a collection of prospectively characterized S. aureus clinical isolates and clinical outcome. METHODOLOGY/PRINCIPAL FINDINGS: Two hundred thirty-nine S. aureus isolates (121 methicillin-resistant S. aureus [MRSA] and 118 methicillin-susceptible S. aureus [MSSA]) were screened by array comparative genomic hybridization (aCGH) to identify genes implicated in complicated infections. After adjustment for multiple tests, 226 genes were significantly associated with severity of infection. Of these 226 genes, 185 were not in the SCCmec element. Within the 185 non-SCCmec genes, 171 were less common and 14 more common in the complicated infection group. Among the 41 genes in the SCCmec element, 37 were more common and 4 were less common in the complicated group. A total of 51 of the 2014 sequences evaluated, 14 non-SCCmec and 37 SCCmec, were identified as genes of interest. CONCLUSIONS/SIGNIFICANCE: Of the 171 genes less common in complicated infections, 152 are of unknown function and may contribute to attenuation of virulence. The 14 non-SCCmec genes more common in complicated infections include bacteriophage-encoded genes such as regulatory factors and autolysins with potential roles in tissue adhesion or biofilm formation
Intrusive Traumatic Re-Experiencing Domain (ITRED) – Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium
Background
Intrusive Traumatic Re-Experiencing Domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective.
Methods
Data was collected from nine sites taking part in the ENIGMA-PTSD Consortium (n=584) and included itemized PTSD symptoms scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and Trauma-exposed (TE)-only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. Random forest classification model was built on a training set using cross-validation (CV), and the averaged CV model performance for classification was evaluated using area-under-the-curve (AUC). The model was tested using a fully independent portion of the data (test dataset), and the test AUC was evaluated.
Results
RsFC signatures differentiated TE-only participants from PTSD and from ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and from ITRED-only participants mainly involved default mode network-related pathways. Some unique features, such as connectivity within the frontal-parietal network, differentiated TE-only participants from one group (PTSD or ITRED-only), but to a lesser extent from the other.
Conclusion
Neural network connectivity supports ITRED as a novel neurobiologically-based approach to classifying post-trauma psychopathology
Field-Caught Permethrin-Resistant Anopheles gambiae Overexpress CYP6P3, a P450 That Metabolises Pyrethroids
Insects exposed to pesticides undergo strong natural selection and have developed various adaptive mechanisms to survive. Resistance to pyrethroid insecticides in the malaria vector Anopheles gambiae is receiving increasing attention because it threatens the sustainability of malaria vector control programs in sub-Saharan Africa. An understanding of the molecular mechanisms conferring pyrethroid resistance gives insight into the processes of evolution of adaptive traits and facilitates the development of simple monitoring tools and novel strategies to restore the efficacy of insecticides. For this purpose, it is essential to understand which mechanisms are important in wild mosquitoes. Here, our aim was to identify enzymes that may be important in metabolic resistance to pyrethroids by measuring gene expression for over 250 genes potentially involved in metabolic resistance in phenotyped individuals from a highly resistant, wild A. gambiae population from Ghana. A cytochrome P450, CYP6P3, was significantly overexpressed in the survivors, and we show that the translated enzyme metabolises both alpha-cyano and non–alpha-cyano pyrethroids. This is the first study to demonstrate the capacity of a P450 identified in wild A. gambiae to metabolise insecticides. The findings add to the understanding of the genetic basis of insecticide resistance in wild mosquito populations
Gold remobilisation and formation of high grade ore shoots driven by dissolution-reprecipitation replacement and Ni substitution into auriferous arsenopyrite
Both gold-rich sulphides and ultra-high grade native gold oreshoots are common but poorly understood phenomenon in orogenic-type mineral systems, partly because fluids in these systems are considered to have relatively low gold solubilities and are unlikely to generate high gold concentrations. The world-class Obuasi gold deposit, Ghana, has gold-rich arsenopyrite spatially associated with quartz veins, which have extremely high, localised concentrations of native gold, contained in microcrack networks within the quartz veins where they are folded. Here, we examine selected samples from Obuasi using a novel combination of quantitative electron backscatter diffraction analysis, ion microprobe imaging, synchrotron XFM mapping and geochemical modelling to investigate the origin of the unusually high gold concentrations. The auriferous arsenopyrites are shown to have undergone partial replacement (~15%) by Au-poor, nickeliferous arsenopyrite, during localised crystal-plastic deformation, intragranular microfracture and metamorphism (340-460 °C, 2 kbars). Our results show the dominant replacement mechanism was pseudomorphic dissolution-reprecipitation, driven by small volumes of an infiltrating fluid that had relatively low fS2 and carried aqueous NiCl2. We find that arsenopyrite replacement produced strong chemical gradients at crystal-fluid interfaces due to an increase in fS2 during reaction, which enabled efficient removal of gold to the fluid phase and development of anomalously gold-rich fluid (potentially 10 ppm or more depending on sulphur concentration). This process was facilitated by precipitation of ankerite, which removed CO2 from the fluid, increasing the relative proportion of sulphur for gold complexation and inhibited additional quartz precipitation. Gold re-precipitation occurred over distances of 10 µm to several tens of metres and was likely a result of sulphur activity reduction through precipitation of pyrite and other sulphides. We suggest this late remobilisation process may be relatively common in orogenic belts containing abundant mafic/ultramafic rocks, which act as a source of Ni and Co scavenged by chloride-bearing fluids. Both the preference of the arsenopyrite crystal structure for Ni and Co, rather than gold, and the release of sulphur during reaction, can drive gold remobilisation in many deposits across broad regions
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