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Temporal variability of microbial response to crude oil exposure in the northern Gulf of Mexico
No full textOil spills are common occurrences in the United States and can result in extensive ecological damage. The 2010 Deepwater Horizon oil spill in the Gulf of Mexico was the largest accidental spill recorded. Many studies were performed in deep water habitats to understand the microbial response to the released crude oil. However, much less is known about how planktonic coastal communities respond to oil spills and whether that response might vary over the course of the year. Understanding this temporal variability would lend additional insight into how coastal Florida habitats may have responded to the Deepwater Horizon oil spill. To assess this, the temporal response of planktonic coastal microbial communities to acute crude oil exposure was examined from September 2015 to September 2016 using seawater samples collected from Pensacola Beach, Florida, at 2-week intervals. A standard oil exposure protocol was performed using water accommodated fractions made from MC252 surrogate oil under photo-oxidizing conditions. Dose response curves for bacterial production and primary production were constructed from 3H-leucine incorporation and 14C-bicarbonate fixation, respectively. To assess drivers of temporal patterns in inhibition, a suite of biological and environmental parameters was measured including bacterial counts, chlorophyll a, temperature, salinity, and nutrients. Additionally, 16S rRNA sequencing was performed on unamended seawater to determine if temporal variation in the in situ bacterial community contributed to differences in inhibition. We observed that there is temporal variation in the inhibition of primary and bacterial production due to acute crude oil exposure. We also identified significant relationships of inhibition with environmental and biological parameters that quantitatively demonstrated that exposure to water-soluble crude oil constituents was most detrimental to planktonic microbial communities when temperature was high, when there were low inputs of total Kjeldahl nitrogen, and when there was low bacterial diversity or low phytoplankton biomass.Virginia Institute of Marine Scienc
Metabolic rate as a predictor of molluscan abundance across the Mid- Pliocene Warm Period in the Virginia Coastal Plain
No full textResting metabolic rate (RMR) is a potentially useful physiological predictor of species' responses to climate warming because it represents the exchange of energy between an organism and its environment. Ectothermic species, like mollusks, will exchange heat energy at faster rates with the environment during warming, and enter a state of decreased respiration, heart rate, and metabolic rate. This allows mollusks with lower RMRs to better conserve energy and survive through periods of higher environmental pressure, including warming. By estimating RMR of fossil mollusks of the Yorktown Formation in Virginia, we can test whether the interaction between temperature and physiology influences fluctuations in molluscan abundance across the Mid-Pliocene Warm Period (MPWP). We hypothesized that bivalves and gastropods with higher RMRs would decrease in abundance across the MPWP. We examined 15 bulk samples from Yorktown Formation localities in southeastern Virginia collected from field sites and the Virginia Museum of Natural History collections. The Yorktown Formation is an ideal study system because: (1) the mollusks are well-preserved and sampled, highly abundant, and taxonomically well- resolved, and (2) paleotemperatures across the MPWP have been reconstructed recently for local outcrops. Each member of the Yorktown Formation represents a period of the MPWP: Sunken Meadow (before), Rushmere (during), and Moore House (after). All bulk samples were sieved, then specimens were sorted, identified using taxonomic monographs, and counted to the species level when possible. For each species present in the Sunken Meadow Member, we estimated RMR using maximum length measurements of species type specimens and pre-warming temperature data derived from recently unpublished paleoclimate reconstruction at the local scale. Genus- and species-level changes in the warming interval show no correlation between RMR and change in percent abundance, but high RMR taxa are more variable in their response to warming. This suggests that high RMR is a high risk/high reward trait, and other factors such as a species' body size, environmental setting, bathymetric range, and geographic range also affect changes in abundance. Understanding species-level responses to MPWP warming (1.8-3.6 Celsius above pre-industrial) may be useful for predicting the response of extant mollusks, particularly those with economically important fisheries, to similar climate warming in the mid-Atlantic U.S. today.Geolog
Inclusive Double Differential Muon Neutrino CC Cross Sections on Various Nuclear Targets in MINERvA
No full textThe Standard Model predicts that neutrinos are massless particles, but the observation of neutrino oscillations between their three existing flavor states is only possible if they possess a small mass. Such mysteries offer exciting opportunities for searches for physics beyond the Standard Model (BSM). Precision neutrino oscillation experiments are one such way to probe neutrino oscillations and search for BSM, but the measurements taken by these experiments are reliant on neutrino interaction models, which introduce a large source of uncertainty. The MINERvA experiment was designed to study neutrino-nucleus interactions on 5 nuclear targets to better constrain these models and subsequently improve the measurements made by neutrino oscillation experiments. This work details an analysis conducted using data from MINERvA to calculate the double differential cross section as a function of longitudinal and transverse muon momentum for inclusive charged current muon neutrino interactions on 3 of the nuclear targets - iron, lead, and carbon. The steps for such a calculation were as follows. Using a medium-energy dataset in which the incident neutrino has an energy between about 2-10 GeV, a series of cuts were applied to obtain a sample of signal events that included both data and simulated Monte Carlo (MC) events. The MC had 2.01E20 protons-on-target (POT), which corresponded to 3,689,661 neutrino events before cuts, while the data had 4.15E19 POT, which corresponded to 1,280,685 events before cuts. The cuts applied were on both the muon kinematics, which were required for reconstruction of the produced muon, and on the material and target within the detector. Then, the background contamination was removed from the signal using a process called sideband fitting that utilized MC simulated events in the regions just outside the nuclear targets to estimate the background and scale the MC appropriately to fit the data. After this, the sources of background interactions, including neutral current and wrong flavor charged current interactions, can be directly subtracted out. An iterative unfolding process was then performed to remove detector smearing effects and ensure that the true transverse and longitudinal momentum values are being properly reconstructed. Lastly, efficiency corrections were applied to account for the true signal events that the detector missed, and the result is normalized with respect to the neutrino flux, the number of target nuclei within the detector, and width of the momentum bins. The resulting cross sections for both data and MC were plotted. Despite large uncertainties, both systematic and statistical, the resulting MC cross sections tended to underestimate the data, which is consistent with previous results. In particular, in regions of low transverse momentum, which are dominated by quasi-elastic and 2p2h interactions, and regions of high momentum, which are dominated by true deep inelastic scattering interactions, the discrepancy between the data and the MC seems to increase. However, running over a larger dataset, in addition to more careful consideration of the uncertainties, will improve the precision of the measurements and allow for more detailed conclusions to be drawn, as well as comparison with different neutrino interaction models. Thus will ultimately help improve those models and the understanding of neutrino interactions.PhysicsBachelors of Science (BS
