Smartbuoy: A marine environmental monitoring buoy with a difference

Mills, David K.; Laane, R.W.P.M.; Rees, J.M.; Loeff, Michiel Rutgers v. d.; Suylen, J.M.; Pearce, David J.; Sivyer, D. B.; Heins, C. F.; Platt, Katie; Rawlinson, M.

doi:10.1016/s0422-9894(03)80050-8

Cited by 29 publications

(24 citation statements)

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“…At each mooring station an automated measuring buoy, called a 'SmartbBuoy', has been deployed as part of the monitoring programs of the United Kingdom and The Netherlands (Mills et al, 2003). The SmartBuoys measured chlorophyll fluorescence, optical backscatter, salinity, temperature and photosynthetically active radiation (PAR) at 1 m depth, using sampling intervals ranging from 12 to 30 min.…”

Section: Automated Measurementsmentioning

confidence: 99%

Predictability and environmental drivers of chlorophyll fluctuations vary across different time scales and regions of the North Sea

Blauw

Benincà

Laane

et al. 2018

Progress in Oceanography

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Predictability and environmental drivers of chlorophyll fluctuations vary across different time scales and regions of the North Sea Blauw, A.N.; Beninca, E.; Laane, R.W.P.M.; Greenwood, N.; Huisman, J. General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. A B S T R A C TPhytoplankton concentrations display strong temporal variability at different time scales. Recent advances in automated moorings enable detailed investigation of this variability. In this study, we analyzed phytoplankton fluctuations at four automated mooring stations in the North Sea, which measured phytoplankton abundance (chlorophyll) and several environmental variables at a temporal resolution of 12-30 min for two to nine years. The stations differed in tidal range, water depth and freshwater influence. This allowed comparison of the predictability and environmental drivers of phytoplankton variability across different time scales and geographical regions. We analyzed the time series using wavelet analysis, cross correlations and generalized additive models to quantify the response of chlorophyll fluorescence to various environmental variables (tidal and meteorological variables, salinity, suspended particulate matter, nitrate and sea surface temperature). Hour-tohour and day-to-day fluctuations in chlorophyll fluorescence were substantial, and mainly driven by sinking and vertical mixing of phytoplankton cells, horizontal transport of different water masses, and non-photochemical quenching of the fluorescence signal. At the macro-tidal stations, these short-term phytoplankton fluctuations were strongly driven by the tides. Along the Dutch coast, variation in salinity associated with the freshwater influence of the river Rhine played an important role, while in the central North Sea variation in weather conditions was a major determinant of phytoplankton variability. At time scales of weeks to months, solar irradiance, nutrient conditions and thermal stratification were the dominant drivers of changes in chlorophyll concentrations. These results show that the dominant drivers of phytoplankton fluctuations differ across marine environments and time scales. Moreover, our findings show that phytoplankton variability on hourly to daily time scales should not be dismissed as environmental noise, but is...

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Section: Automated Measurementsmentioning

confidence: 99%

Predictability and environmental drivers of chlorophyll fluctuations vary across different time scales and regions of the North Sea

Blauw

Benincà

Laane

et al. 2018

Progress in Oceanography

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“…Continuous time series of temperature, chlorophyll a (chl a) concentration, turbidity and oxygen concentration were obtained at three different water depths (1 m, 35 m, 45 m) from CEFAS smartbuoys (Mills et al, 2003). Chlorophyll fluorescence was determined using a chlorophyll fluorometer (Seapoint Inc., USA) and turbidity with a turbidity meter (Seapoint Inc., USA) with a 1 Hz frequency.…”

Section: Geochemical Data Setmentioning

confidence: 99%

Impact of global change on coastal oxygen dynamics and risk of hypoxia

2013

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Climate change and changing nutrient loadings are the two main aspects of global change that are linked to the increase in the prevalence of coastal hypoxia – the depletion of oxygen in the bottom waters of coastal areas. However, it remains uncertain how strongly these two drivers will each increase the risk of hypoxia over the next decades. Through model simulations we have investigated the relative influence of climate change and nutrient run-off on the bottom water oxygen dynamics in the Oyster Grounds, an area in the central North Sea experiencing summer stratification. Simulations were performed with a one-dimensional ecosystem model that couples hydrodynamics, pelagic biogeochemistry and sediment diagenesis. Climatological conditions for the North Sea over the next 100 yr were derived from a global-scale climate model. Our results indicate that changing climatological conditions will increase the risk of hypoxia. The bottom water oxygen concentration in late summer is predicted to decrease by 24 μM or 11.5% in the year 2100. More intense stratification is the dominant factor responsible for this decrease (58%), followed by the reduced solubility of oxygen at higher water temperature (27%), while the remaining part could be attributed to enhanced metabolic rates in warmer bottom waters (15%). Relative to these climate change effects, changes in nutrient runoff are also important and may even have a stronger impact on the bottom water oxygenation. Decreased nutrient loadings strongly decrease the probability of hypoxic events. This stresses the importance of continued eutrophication management in coastal areas, which could function as a mitigation tool to counteract the effects of rising temperatures

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“…Optical backscatter in formazine turbidity units (FTU) are collected continuously by the Seapoint turbidity metre on the surface SmartBuoys (Mills et al 2003) with a high frequency time step of 30 min, between 1 and 2 m below the water surface (Mills et al 2005). The turbidity metre measures the light scattered by particles in the scatterance angles of 15°to 150°from a light source emitted at 880 nm.…”

Section: Cefas Time Seriesmentioning

confidence: 99%

Reconstruction of MODIS total suspended matter time series maps by DINEOF and validation with autonomous platform data

et al. 2011

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In situ measurements of total suspended matter (TSM) over the period [2003][2004][2005][2006], collected with two autonomous platforms from the Centre for Environment, Fisheries and Aquatic Sciences (Cefas) measuring the optical backscatter (OBS) in the southern North Sea, are used to assess the accuracy of TSM time series extracted from satellite data. Since there are gaps in the remote sensing (RS) data, due mainly to cloud cover, the Data Interpolating Empirical Orthogonal Functions (DINEOF) is used to fill in the TSM time series and build a continuous daily "recoloured" dataset. The RS datasets consist of TSM maps derived from MODIS imagery using the bio-optical model of Nechad et al. (Rem Sens Environ 114: 854-866, 2010). In this study, the DINEOF time series are compared to the in situ OBS measured in moderately to very turbid waters respectively in West Gabbard and Warp Anchorage, in the southern North Sea. The discrepancies between instantaneous RS, DINEOFfilled RS data and Cefas data are analysed in terms of TSM algorithm uncertainties, space-time variability and DINEOF reconstruction uncertainty.

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Smartbuoy: A marine environmental monitoring buoy with a difference

Cited by 29 publications

References 0 publications

Predictability and environmental drivers of chlorophyll fluctuations vary across different time scales and regions of the North Sea

Predictability and environmental drivers of chlorophyll fluctuations vary across different time scales and regions of the North Sea

Impact of global change on coastal oxygen dynamics and risk of hypoxia

Reconstruction of MODIS total suspended matter time series maps by DINEOF and validation with autonomous platform data

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