Benthic O2 uptake of two cold-water coral communities estimated with the non-invasive eddy correlation technique

Rovelli, Lorenzo; Attard, Karl M.; Bryant, Lee D.; Flögel, Sascha; Ståhl, Henrik; Roberts, J. Murray; Линке, Петер; Glud, Ronnie N.

doi:10.3354/meps11211

Cited by 50 publications

(58 citation statements)

References 33 publications

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“…6b). The relatively large average time shift which had an average of 1.11 s was not expected because Clark-type electrodes used for eddy covariance typically have response times (t 90% ) between 0.2 and 0.5 s Attard et al, 2014;Rovelli et al, 2015). The most likely reason for the large shift is that the electrode tip was damaged or coated with phyto-detritus or marine mucilage near the beginning of the deployment, notably at min ∼ 460 (Fig.…”

Section: Discussionmentioning

confidence: 95%

“…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%

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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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Section: Discussionmentioning

confidence: 95%

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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“…TOU can be measured through either ex situ whole core incubations, in situ chamber lander incubations or through non-invasive in situ Eddy Covariance lander measurements (e.g. Berelson et al 2003;Berg et al 2007;Rovelli et al 2015). However, studies comparing ex situ incubation set ups with in situ measurements have found that the former can be representative of the benthic study site, provided they are run at in situ temperature and the overlying incubated water is well mixed Tengberg et al 2004).…”

Section: Introductionmentioning

confidence: 99%

Oxygen dynamics in shelf seas sediments incorporating seasonal variability

et al. 2017

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Shelf sediments play a vital role in global biogeochemical cycling and are particularly important areas of oxygen consumption and carbon mineralisation. Total benthic oxygen uptake, the sum of diffusive and faunal mediated uptake, is a robust proxy to quantify carbon mineralisation. However, oxygen uptake rates are dynamic, due to the diagenetic processes within the sediment, and can be spatially and temporally variable. Four benthic sites in the Celtic Sea, encompassing gradients of cohesive to permeable sediments, were sampled over four cruises to capture seasonal and spatial changes in oxygen dynamics. Total oxygen uptake (TOU) rates were measured through a suite of incubation experiments and oxygen microelectrode profiles were taken across all four benthic sites to provide the oxygen penetration depth and diffusive oxygen uptake (DOU) rates. The difference between TOU and DOU allowed for quantification of the fauna mediated oxygen uptake and diffusive uptake. High resolution measurements showed clear seasonal and spatial trends, with higher oxygen uptake rates measured in cohesive sediments compared to the permeable sediment. The significant differences in oxygen dynamics between the sediment types were consistent between seasons, with increasing oxygen consumption during and after the phytoplankton bloom. Carbon mineralisation in shelf sediments is strongly influenced by sediment type and seasonality.

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“…The two manipulators and a customized tool skid, which may be modi ed to accommodate di erent tools, are used for sampling, for example, rocks, fauna, uids and sediments. Furthermore, ROV PHOCA was used to assemble and re-assemble the MoLab landers (Rovelli et al, 2015) and recover long-term sensor records from deepsea bore hole observatories (Figure 1f). …”

Section: Introductionmentioning

confidence: 99%

“…ROV PHOCA has been deployed in various environments like the shallow waters of the North Sea (Vielstädte et al, 2015), the North Atlantic o Norway (Flögel et al, 2014;Rovelli et al, 2015) and Iceland, the Mediterranean (Jordt et al, 2015;Schmidt et al, 2015) as well as in the Paci c o Japan. The ROV system comprises the ROV itself, a Launch and Recovery System (LARS), winches and cables as well as one control and power container depending on the con guration and the capabilities of the supporting research vessels.…”

Section: Introductionmentioning

confidence: 99%

Remotely Operated Vehicle “ROV PHOCA“

Abegg

Линке

2017

JLSRF

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The remotely operated vehicle ROV PHOCA is a deep diving platform rated for water depths of 3000 meters. The ROV is linked to a surface vessel via an umbilical cable transmitting power (copper wires) and data (3 single-mode glass bers). As standard it comes equipped with still and video cameras and two di erent manipulators providing eyes and hands in the deep. Special emphasis was put on the compatibility of numerous systems with the existing ROV KIEL 6000 to facilitate the use of both systems on various research vessels with a given team of ROV pilots. Besides this, a set of other tools may be added depending on the mission tasks, ranging from simple manipulative tools as chisels and shovels to electrically connected instruments which can send insitu data to the ship through the ROVs network, allowing immediate decisions upon manipulation or sampling strategies.

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Benthic O2 uptake of two cold-water coral communities estimated with the non-invasive eddy correlation technique

Cited by 50 publications

References 33 publications

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

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

Oxygen dynamics in shelf seas sediments incorporating seasonal variability

Remotely Operated Vehicle “ROV PHOCA“

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