Browsing by Author "Stoskopf, MK"

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    NMR metabolomic analysis of skeletal muscle, heart, and liver of hatchling loggerhead sea turtles (caretta caretta) experimentally exposed to crude oil and/or corexit
    (Metabolites, 2019-02-01) Bembenek-Bailey, SA; Niemuth, JN; McClellan-Green, PD; Godfrey, MH; Harms, CA; Gracz, H; Stoskopf, MK
    © 2019 by the authors. Licensee MDPI, Basel, Switzerland. We used nuclear magnetic spectroscopy (NMR) to evaluate the metabolic impacts of crude oil, Corexit 5900A, a dispersant, and a crude oil Corexit 5900A mixture exposure on skeletal muscle, heart, and liver physiology of hatchling loggerhead sea turtles (Caretta caretta). Tissue samples were obtained from 22 seven-day-old hatchlings after a four day cutaneous exposure to environmentally relevant concentrations of crude oil, Corexit 5900A, a combination of crude oil and Corexit 9500A, or a seawater control. We identified 38 metabolites in the aqueous extracts of the liver, and 30 metabolites in both the skeletal and heart muscle aqueous extracts, including organic acids/osmolytes, energy compounds, amino acids, ketone bodies, nucleosides, and nucleotides. Skeletal muscle lactate, creatines, and taurine concentrations were significantly lower in hatchlings exposed to crude oil than in control hatchlings. Lactate, taurine, and cholines appeared to be the basis of some variation in hatchling heart samples, and liver inosine, uracil, and uridine appeared to be influenced by Corexit and crude oil exposure. Observed decreases in concentrations of lactate and creatines may reflect energy depletion in skeletal muscle of oil-exposed animals, while decreased taurine concentrations in these animals may reflect higher oxidative stress.
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    1H-nmr metabolomic study of whole blood from hatchling loggerhead sea turtles (Caretta caretta) exposed to crude oil and/or corexit
    (Royal Society Open Science, 2017-11-22) Bembenek Bailey, SA; Niemuth, JN; McClellan-Green, PD; Godfrey, MH; Harms, CA; Stoskopf, MK
    © 2017 The Authors. We used proton nuclear magnetic resonance spectroscopy (1H-NMR) to evaluate metabolic impacts of environmentally relevant crude oil and Corexit exposures on the physiology of hatchling loggerhead sea turtles (Caretta caretta). Sample extraction and data acquisition methods for very small volume whole blood samples and sources of variation between individual hatchlings were assessed. Sixteen unclotted, whole blood samples were obtained from 7-day-old hatchlings after a 4-day cutaneous exposure to either control seawater, crude oil, Corexit 9500A or a combination of crude oil and Corexit 9500A. After extraction, one- and two-dimensional 1 H-NMR spectra of the samples were obtained, and 17 metabolites were identified and confirmed in the whole blood spectra. Variation among samples due to the concentrations of metabolites 3-hydroxybutyrate, lactate, trimethylamine oxide and propylene glycol did not statistically correlate with treatment group. However, the characterization of the hatchling loggerhead whole blood metabolome provides a foundation for future metabolomic research with sea turtles and a basis for the study of tissues from exposed hatchling sea turtles.
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    Using random forest algorithm to model cold-stunning events in sea turtles in North Carolina
    (Journal of Fish and Wildlife Management, 2020-12-01) Niemuth, JN; Ransom, CC; Finn, SA; Godfrey, MH; Nelson, SAC; Stoskopf, MK
    © 2020 U.S. Fish and Wildlife Service. All rights reserved. Sea turtle strandings due to cold-stunning are seen when turtles are exposed to ocean temperatures that acutely and persistently drop below approximately 128C. In North Carolina, this syndrome affects imperiled loggerhead Caretta caretta, green Chelonia mydas, and Kemp’s ridley Lepidochelys kempii sea turtle species. Based on oceanic and meteorological patterns of cold-stunning in sea turtles, we hypothesized that we could predict the daily size of cold-stunning events in North Carolina using random forest models. We used cold-stunning data from the North Carolina Sea Turtle Stranding and Salvage Network from 2010 to 2015 and oceanic and meteorological data from the National Data Buoy Center from 2009 to 2015 to create a random forest model that explained 99% of the variance. We explored additional models using the 10 and 20 most important variables or only oceanic and meteorological variables. These models explained similar percentages of variance. The variables most frequently found to be important were related to air temperature, atmospheric pressure, wind direction, and wind speed. Surprisingly, variables associated with water temperature, which is critical from a biological perspective, were not among the most important variables identified. We also included variables for the mean change in these metrics daily from 4 d before the day of stranding. These variables were among the most important in several of our models, especially the change in mean air temperature from 4 d before stranding to the day of stranding. The importance of specific variables from our random forest models can be used to guide the selection of future model predictors to estimate daily size of cold-stunning events. We plan to apply the results of this study to a predictive model that can serve as a warning system and to a downscaled climate projection to determine the potential impact of climate change on cold-stunning event size in the future.