Eddy correlation measurements of oxygen uptake in deep ocean sediments

Berg, Peter; Glud, Ronnie N.; Hume, Andrew; Ståhl, Henrik; Oguri, Kazuta; Meyer, Volker; Kitazato, Hiroshi

doi:10.4319/lom.2009.7.576

Cited by 87 publications

(108 citation statements)

References 24 publications

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“…The fluctuating components were separated from the means by Reynolds decomposition as u z = u z − u z and C = C − C where u z and C are the instantaneous measurements, and the means (u z and C) were determined by linear least squares fits (linear detrending) over each 0.25 h interval (Berg et al, 2009). The three-dimensional velocity field was rotated to orient the x-axis into the mean flow direction and to bring the mean vertical velocities to zero to correct for any sensor tilt.…”

Section: Discussionmentioning

confidence: 99%

“…Oxygen eddy correlation systems have been used to determine photosynthesis and respiration in muddy marine benthic systems and river bottoms (Berg et al, 2003), sandy sediments (Kuwae et al, 2006;Berg and Huettel, 2008;Reimers et al, 2012), the deep ocean (Berg et al, 2009), lakes McGinnis et al, 2008;Lorrai et al, 2010), hard-bottom arctic substrates , and seagrass beds (Hume et al, 2011). With the eddy correlation technique measurements are conducted under true in situ conditions, i.e.…”

Section: H Long Et Al: Oxygen Exchange and Ice Melt By Eddy Corrmentioning

confidence: 99%

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Oxygen exchange and ice melt measured at the ice-water interface by eddy correlation

et al. 2012

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Abstract. This study examined fluxes across the ice-water interface utilizing the eddy correlation technique. Temperature eddy correlation systems were used to determine rates of ice melting and freezing, and O 2 eddy correlation systems were used to examine O 2 exchange rates driven by biological and physical processes. The study was conducted below 0.7 m thick sea-ice in mid-March 2010 in a southwest Greenland fjord and revealed low rates of ice melt at a maximum of 0.80 mm d −1 . The O 2 flux associated with release of O 2 depleted melt water was less than 13 % of the average daily O 2 respiration rate. Ice melt and insufficient vertical turbulent mixing due to low current velocities caused periodic stratification immediately below the ice. This prevented the determination of fluxes 61 % of the deployment time. These time intervals were identified by examining the velocity and the linearity and stability of the cumulative flux. The examination of unstratified conditions through vertical velocity and O 2 spectra and their cospectra revealed characteristic fingerprints of well-developed turbulence. From the measured O 2 fluxes a photosynthesis/irradiance curve was established by least-squares fitting. This relation showed that light limitation of net photosynthesis began at 4.2 µmol photons m −2 s −1 , and that algal communities were well-adapted to low-light conditions as they were light saturated for 75 % of the day during this early spring period. However, the sea-ice associated microbial and algal community was net heterotrophic with a daily gross primary production of 0.69 mmol O 2 m −2 d −1 and a respiration rate of −2.13 mmol O 2 m −2 d −1 leading to a net ecosystem metabolism of −1.45 mmol O 2 m −2 d −1 . This application of the eddy correlation technique produced high temporal resolution O 2 fluxes and ice melt rates that were measured without disturbing the in situ environmental conditions while integrating over an area of approximately 50 m 2 which incorporated the highly variable activity and spatial distributions of sea-ice communities.

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Section: Discussionmentioning

confidence: 99%

Section: H Long Et Al: Oxygen Exchange and Ice Melt By Eddy Corrmentioning

confidence: 99%

Oxygen exchange and ice melt measured at the ice-water interface by eddy correlation

et al. 2012

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“…The identified time shifts, one for each burst, varied with the mean current velocity and its direction, but averaged over all deployments, this correction increased the flux by 25 % (McGinnis et al 2008;Lorrai et al 2010;Donis et al 2015). The O 2 fluxes, in mmol m -2 day -1 , were then extracted from the vertical ADV velocity (w) and the measured O 2 concentrations (C) as the covariance w 0 C 0 , where the fluctuation components, w 0 and C 0 , are deviations from a least-squares linear fit to the data in each burst (Lee et al 2004;Berg et al 2009). The variation in the derived EOE was quantified by both the SD and standard error of the burst values during the respective deployments.…”

Section: Eddy Covariance Measurementsmentioning

confidence: 99%

Benthic Carbon Mineralization and Nutrient Turnover in a Scottish Sea Loch: An Integrative In Situ Study

et al. 2016

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Based on in situ microprofiles, chamber incubations and eddy covariance measurements, we investigated the benthic carbon mineralization and nutrient regeneration in a *65-m-deep sedimentation basin of Loch Etive, UK. The sediment hosted a considerable amount of infauna that was dominated by the brittle star A. filiformis. The numerous burrows were intensively irrigated enhancing the benthic in situ O 2 uptake by *50 %, and inducing highly variable redox conditions and O 2 distribution in the surface sediment as also documented by complementary laboratory-based planar optode measurements. The average benthic O 2 exchange as derived by chamber incubations and the eddy covariance approach were similar (14.9 ± 2.5 and 13.1 ± 9.0 mmol m -2 day -1 ) providing confidence in the two measuring approaches. Moreover, the non-invasive eddy approach revealed a flow-dependent benthic O 2 flux that was partly ascribed to enhanced ventilation of infauna burrows during periods of elevated flow rates. The ratio in exchange rates of RCO 2 and O 2 was close to unity, confirming that the O 2 uptake was a good proxy for the benthic carbon mineralization in this setting. The infauna activity resulted in highly dynamic redox conditions that presumably facilitated an efficient degradation of both terrestrial and marine-derived organic material. The complex O 2 dynamics of the burrow environment also concurrently stimulated nitrification and coupled denitrification rates making the sediment an efficient sink for bioavailable nitrogen. Furthermore, bioturbation mediated a high efflux of dissolved phosphorus and silicate. The study documents a high spatial and temporal variation in benthic solute exchange with important implications for benthic turnover of organic carbon and nutrients. However, more long-term in situ investigations with like approaches are required to fully understand how environmental events and spatio-temporal variations interrelate to the overall biogeochemical functioning of coastal sediments.

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“…The eddy flux itself (Fig. 4b, c) was calculated following standard flux calculation procedures based on linear de-trending (Lee et al, 2004;Berg et al, 2009;Attard et al, 2014). Therefore, the estimated eddy flux represents the real flux plus any time lag bias.…”

Section: Illustration Of New Time Lag Correction Using Wave Model Datamentioning

confidence: 99%

“…Over the last 10 years, the aquatic eddy covariance technique has become a widely accepted approach for measuring oxygen fluxes between benthic ecosystems and the overlying water . In that time, the number of users has grown rapidly, and the technique has been applied under very different field settings such as muddy and sandy sediments Kuwae et al, 2006;Glud et al, 2010), deep ocean sediments (Berg et al, 2009), coral reefs Cathalot et al, 2015;Rovelli et al, 2015), and seagrass meadows (Hume et al, 2011;Rheuban et al, 2014;Long et al, 2015). With a few exceptions, all of the recently published aquatic eddy covariance studies have focused on oxygen fluxes.…”

Section: Introductionmentioning

confidence: 99%

Technical note: Time lag correction of aquatic eddy covariance data measured in the presence of waves

et al. 2015

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Abstract. Extracting benthic oxygen fluxes from eddy covariance time series measured in the presence of surface gravity waves requires careful consideration of the temporal alignment of the vertical velocity and the oxygen concentration. Using a model based on linear wave theory and measured eddy covariance data, we show that a substantial error in flux can arise if these two variables are not aligned correctly in time. We refer to this error in flux as the time lag bias. In one example, produced with the wave model, we found that an offset of 0.25 s between the oxygen and the velocity data produced a 2-fold overestimation of the flux. In another example, relying on nighttime data measured over a seagrass meadow, a similar offset reversed the flux from an uptake of −50 mmol m −2 d −1 to a release of 40 mmol m −2 d −1 . The bias is most acute for data measured at shallow-water sites with short-period waves and low current velocities. At moderate or higher current velocities (> 5-10 cm s −1 ), the bias is usually insignificant. The widely used traditional time shift correction for data measured in unidirectional flows, where the maximum numerical flux is sought, should not be applied in the presence of waves because it tends to maximize the time lag bias or give unrealistic flux estimates. Based on wave model predictions and measured data, we propose a new time lag correction that minimizes the time lag bias. The correction requires that the time series of both vertical velocity and oxygen concentration contain a clear periodic wave signal. Because wave motions are often evident in eddy covariance data measured at shallow-water sites, we encourage more work on identifying new time lag corrections.

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Eddy correlation measurements of oxygen uptake in deep ocean sediments

Cited by 87 publications

References 24 publications

Oxygen exchange and ice melt measured at the ice-water interface by eddy correlation

Oxygen exchange and ice melt measured at the ice-water interface by eddy correlation

Benthic Carbon Mineralization and Nutrient Turnover in a Scottish Sea Loch: An Integrative In Situ Study

Technical note: Time lag correction of aquatic eddy covariance data measured in the presence of waves

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