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|Ilicak, M., Drange, H., Wang, Q., Gerdes, R., Aksenov, Y., Bailey, D., et al. (2016). An assessment of the Arctic Ocean in a suite of interannual CORE-II simulations. Part III: Hydrography and fluxes. Ocean Modelling, 100, 141–161.|
|Karmel, T. (2016). Using multiple methodologies to explore variation in rainfall events in the southeastern United States. Bachelor's thesis, Florida State University, Tallahassee, FL.|
|Kipkogei, O., Bhardwaj, A., Kumar, V., Ogallo, L. A., Opijah, F. J., Mutemi, J. N., et al. (2016). Improving multimodel medium range forecasts over the Greater Horn of Africa using the FSU superensemble. Meteorol Atmos Phys, 128(4), 441–451.|
|Kozar, M. E., Misra, V., & Powell, M. D. (2016). Hindcasts of Integrated Kinetic Energy in Atlantic Tropical Cyclones: A Neural Network Prediction Scheme. Mon. Wea. Rev., 144(12), 4591–4603.|
Krause, J. W., Stukel, M. R., Taylor, A. G., Taniguchi, D. A. A., De Verneil, A., & Landry, M. R. (2016). Net biogenic silica production and the contribution of diatoms to new production and organic matter export in the Costa Rica Dome ecosystem. J Plankton Res, 38(2), 216–229.
Abstract: We determined the net rate of biogenic silica (bSiO2) production and estimated the diatom contribution to new production and organic matter export in the Costa Rica Dome during summer 2010. The shallow thermocline significantly reduces bSiO2 dissolution rates below the mixed layer, leading to significant enhancement of bSiO2 relative to organic matter (silicate-pump condition). This may explain why deep export of bSiO2 in this region is elevated by an order of magnitude relative to comparable systems. Diatom carbon, relative to autotrophic carbon, was low (<3%); however, the contribution of diatoms to new production averaged 3 and 13% using independent approaches. The 4-old discrepancy between methods may be explained by a low average C:Si ratio ( approximately 1.4) for the net produced diatom C relative to the net produced bSiO2. We speculate that this low production ratio is not the result of reduced C, but may arise from a significant contribution of non-diatom silicifying organisms to bSiO2 production. The contribution of diatoms to organic matter export was minor (5.7%). These results, and those of the broader project, suggest substantial food-web transformation of diatom organic matter in the euphotic zone, which creates enriched bSiO2 relative to organic matter within the exported material.
Keywords: biogenic silica production; diatom; new production; vertical flux
|Krishnamurti, T. N., Kumar, V., Simon, A., Bhardwaj, A., Ghosh, T., & Ross, R. (2016). A review of multimodel superensemble forecasting for weather, seasonal climate, and hurricanes. Rev. Geophys., 54(2), 336–377.|
Landry, M. R., Selph, K. E., Decima, M., Gutierrez-Rodriguez, A., Stukel, M. R., Taylor, A. G., et al. (2016). Phytoplankton production and grazing balances in the Costa Rica Dome. J Plankton Res, 38(2), 366–379.
Abstract: We investigated phytoplankton production rates and grazing fates in the Costa Rica Dome (CRD) during summer 2010 based on dilution depth profiles analyzed by flow cytometry and pigments and mesozooplankton grazing assessed by gut fluorescence. Three community production estimates, from 14C uptake (1025 +/- 113 mg C m-2 day-1) and from dilution experiments analyzed for total Chla (990 +/- 106 mg C m-2 day-1) and flow cytometry populations (862 +/- 71 mg C m-2 day-1), exceeded regional ship-based values by 2-3-fold. Picophytoplankton accounted for 56% of community biomass and 39% of production. Production profiles extended deeper for Prochlorococcus (PRO) and picoeukaryotes than for Synechococcus (SYN) and larger eukaryotes, but 93% of total production occurred above 40 m. Microzooplankton consumed all PRO and SYN growth and two-third of total production. Positive net growth of larger eukaryotes in the upper 40 m was balanced by independently measured consumption by mesozooplankton. Among larger eukaryotes, diatoms contributed approximately 3% to production. On the basis of this analysis, the CRD region is characterized by high production and grazing turnover, comparable with or higher than estimates for the eastern equatorial Pacific. The region nonetheless displays characteristics atypical of high productivity, such as picophytoplankton dominance and suppressed diatom roles.
Keywords: grazing; plankton community; productivity
|Leadbetter, A. M., Shepherd, A., Arko, R., Chandler, C., Chen, Y., Dockery, N., et al. (2016). Experiences of a “semantics smackdown”. Earth Sci Inform, 9(3), 355–363.|
|Liu, J., Feld, D., Xue, Y., Garcke, J., Soddemann, T., & Pan, P. (2016). An efficient geosciences workflow on multi-core processors and GPUs: a case study for aerosol optical depth retrieval from MODIS satellite data. International Journal of Digital Earth, 9(8), 748–765.|
Lobodin, V. V., Maksimova, E. V., & Rodgers, R. P. (2016). Gas Chromatography/Atmospheric Pressure Chemical Ionization Tandem Mass Spectrometry for Fingerprinting the Macondo Oil Spill. Anal Chem, 88(13), 6914–6922.
Abstract: We report the first application of a new mass spectrometry technique (gas chromatography combined to atmospheric pressure chemical ionization tandem mass spectrometry, GC/APCI-MS/MS) for fingerprinting a crude oil and environmental samples from the largest accidental marine oil spill in history (the Macondo oil spill, the Gulf of Mexico, 2010). The fingerprinting of the oil spill is based on a trace analysis of petroleum biomarkers (steranes, diasteranes, and pentacyclic triterpanes) naturally occurring in crude oil. GC/APCI enables soft ionization of petroleum compounds that form abundant molecular ions without (or little) fragmentation. The ability to operate the instrument simultaneously in several tandem mass spectrometry (MS/MS) modes (e.g., full scan, product ion scan, reaction monitoring) significantly improves structural information content and sensitivity of analysis. For fingerprinting the oil spill, we constructed diagrams and conducted correlation studies that measure the similarity between environmental samples and enable us to differentiate the Macondo oil spill from other sources.