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Full-Text Articles in Other Oceanography and Atmospheric Sciences and Meteorology

Radiocarbon Analyses Quantify Peat Carbon Losses With Increasing Temperature In A Whole Ecosystem Warming Experiment, Rachel M. Wilson, Natalie A. Griffiths, Ate Visser, Karis J. Mcfarlane, Stephen D. Sebestyen, Keith C. Oleheiser, Samantha Bosman, Anya M. Hopple, Malak M. Tfaily, Randall K. Kolka, Paul J. Hanson, Joel E. Kostka, Scott D. Bridgham, Jason K. Keller, Jeffrey P. Chanton Oct 2021

Radiocarbon Analyses Quantify Peat Carbon Losses With Increasing Temperature In A Whole Ecosystem Warming Experiment, Rachel M. Wilson, Natalie A. Griffiths, Ate Visser, Karis J. Mcfarlane, Stephen D. Sebestyen, Keith C. Oleheiser, Samantha Bosman, Anya M. Hopple, Malak M. Tfaily, Randall K. Kolka, Paul J. Hanson, Joel E. Kostka, Scott D. Bridgham, Jason K. Keller, Jeffrey P. Chanton

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Climate warming is expected to accelerate peatland degradation and release rates of carbon dioxide (CO2) and methane (CH4). Spruce and Peatlands Responses Under Changing Environments is an ecosystem-scale climate manipulation experiment, designed to examine peatland ecosystem response to climate forcings. We examined whether heating up to +9 °C to 3 m-deep in a peat bog over a 7-year period led to higher C turnover and CO2 and CH4 emissions, by measuring 14C of solid peat, dissolved organic carbon (DOC), CH4, and dissolved CO2 (DIC). DOC, a major substrate for heterotrophic respiration, increased significantly with warming. There was no 7-year trend …


Predicting Spatial Patterns In Precipitation Isotope (Δ2h And Δ18o) Seasonality Using Sinusoidal Isoscapes, Scott T. Allen, James W. Kirchner, Gregory R. Goldsmith May 2018

Predicting Spatial Patterns In Precipitation Isotope (Δ2h And Δ18o) Seasonality Using Sinusoidal Isoscapes, Scott T. Allen, James W. Kirchner, Gregory R. Goldsmith

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Understanding how precipitation isotopes vary spatially and temporally is important for tracer applications. We tested how well month‐to‐month variations in precipitation δ18O and δ2H were captured by sinusoidal cycles, and how well spatial variations in these seasonal cycles could be predicted, across Switzerland. Sine functions representing seasonal cycles in precipitation isotopes explained between 47% and 94% of the variance in monthly δ18O and δ2H values at each monitoring site. A significant sinusoidal cycle was also observed in line‐conditioned excess. We interpolated the amplitudes, phases, and offsets of these sine functions across the landscape, using multiple linear …


An Assessment Of Atmospheric And Meteorological Factors Regulating Red Sea Phytoplankton Growth, Wenzhao Li, Hesham El-Askary, Mohamed A. Qurban, Emmanouil Proestakis, Michael J. Garay, Olga V. Kalishnikova, Vassilis Amiridis, Antonis Gkikas, Eleni Marinou, Thomas Piechota, K. P. Manikandan Apr 2018

An Assessment Of Atmospheric And Meteorological Factors Regulating Red Sea Phytoplankton Growth, Wenzhao Li, Hesham El-Askary, Mohamed A. Qurban, Emmanouil Proestakis, Michael J. Garay, Olga V. Kalishnikova, Vassilis Amiridis, Antonis Gkikas, Eleni Marinou, Thomas Piechota, K. P. Manikandan

Mathematics, Physics, and Computer Science Faculty Articles and Research

This study considers the various factors that regulate nutrients supply in the Red Sea. Multi-sensor observation and reanalysis datasets are used to examine the relationships among dust deposition, sea surface temperature (SST), and wind speed, as they may contribute to anomalous phytoplankton blooms, through time-series and correlation analyses. A positive correlation was found at 0–3 months lag between chlorophyll-a (Chl-a) anomalies and dust anomalies over the Red Sea regions. Dust deposition process was further examined with dust aerosols’ vertical distribution using satellite lidar data. Conversely, a negative correlation was found at 0–3 months lag between SST anomalies …