Functioning of microphytobenthos in estuaries

Abstract The benthic primary production of subtidal coastal sediments is grossly under sampled -especially in relation to its potential importance. This is partly due to lack of appropriate measuring techniques. Microsensor approaches represent a strong tool for describing and quantifying microscale benthic photosynthesis and related processes, however, spatial and temporal extrapolation from single point measurements in heterogeneous subtidal sediments is complicated. Complementary use of chambers and 14 C incubations can be helpful but these approaches have their own caveats and limitations. New approaches such as in situ PAM measurements and in situ PAM imagine may turn out to be very helpful in extrapolating microsensor data to larger scales -and robust intercalibrations between the techniques have been presented. Planar O 2 optodes and O 2 eddy-correlation measurements represent other very promising in situ approaches that overcome the limitations of microscale techniques for accessing benthic primary production. The present manuscript gives a brief review on available microscale techniques for quantifying subtidal benthic primary production Introduction The potential importance of subtidal benthic microphytes for local, regional and global carbon cycling is becoming increasingly recognized. In 2003, there existed a little more than 100 studies quantifying the benthic primary production in marine areas but most of these most have been performed in the intertidal zone (Cahoon 1999). Subtidal studies amount to less than 40 and only around 10 studies have been performed at water depth >5 m. Only 4 studies have been conducted in the Arctic area, hosting the relatively largest area of shallow-water, shelf sediment. Our current database on benthic microphytic activity in subtidal areas is very limited. Apart from the relative few studies on benthic microphytic activity, the use of various techniques; 14 C-incubations, chamber incubations and microsensor approaches hamper the assessment of benthic microphytes activity. The 14 C incubation in principle measures the gross photosynthesis, however, inaccurate determination of the specifi c activity or slurry procedures at the best allow only a crude Functioning of microphytobenthos in estuaries

Estimating primary production from oxygen time series: A novel approach in the frequency domain

Based on an analysis in the frequency domain of the governing equation of oxygen dynamics in aquatic systems, we derive a new method for estimating gross primary production (GPP) from oxygen time series. The central result of this article is a relation between time averaged GPP and the amplitude of the diel harmonic in an oxygen time series. We call this relation the Fourier method for estimating GPP. To assess the performance and accuracy of the method, we generate synthetic oxygen time series with a series of gradually more complex models, and compare the result with simulated GPP. We demonstrate that the method is applicable in systems with a range of rates of mixing, air–water exchange and primary production. We also apply the new method to oxygen time series from the Scheldt estuary (Belgium) and compare it with 14C-based GPP measurements. We demonstrate the Fourier method is particularly suited for estimating GPP in estuarine and coastal systems where tidal advection has a large imprint in observed oxygen concentrations. As such it enlarges the number of systems where GPP can be estimated from in situ oxygen concentrations. By shifting the focus to the frequency domain, we also gain some useful insights on the effect of observational error and of stochastic drivers of oxygen dynamics on metabolic estimates derived from oxygen time series

Imaging-in-flow: digital holographic microscopy as a novel tool to detect and classify nanoplanktonic organisms

Traditional taxonomic identification of planktonic organisms is based on light microscopy, which is both time-consuming and tedious. In response, novel ways of automated (machine) identification, such as flow cytometry, have been investigated over the last two decades. To improve the taxonomic resolution of particle analysis, recent developments have focused on "imaging-in-flow," i.e., the ability to acquire microscopic images of planktonic cells in a flow-through mode. Imaging-in-flow systems are traditionally based on classical brightfield microscopy and are faced with a number of issues that decrease the classification performance and accuracy (e. g., projection variance of cells, migration of cells out of the focus plane). Here, we demonstrate that a combination of digital holographic microscopy (DHM) with imaging-in-flow can improve the detection and classification of planktonic organisms. In addition to light intensity information, DHM provides quantitative phase information, which generates an additional and independent set of features that can be used in classification algorithms. Moreover, the capability of digitally refocusing greatly increases the depth of field, enables a more accurate focusing of cells, and reduces the effects of position variance. Nanoplanktonic organisms similar in shape were successfully classified from images captured with an off-axis DHM with partial coherence. Textural features based on DHM phase information proved more efficient in separating the three tested phytoplankton species compared with shape-based features or textural features based on light intensity. An overall classification score of 92.4% demonstrates the potential of holographic-based imaging-in-flow for similar looking organisms in the nanoplankton range

Calibration and Validation of the Sentinels Geophysical Observation Models

We present a method to calibrate and validate observational models that interrelate remotely sensed energy fluxes to geophysical variables of land and water surfaces. Coincident sets of remote sensing observation of visible and microwave radiations and geophysical data are assembled and subdivided into calibration (Cal) and validation (Val) data sets. Each Cal/Val pair is used to derive the coefficients (from the Cal set) and the accuracy (from the Val set) of the observation model. Combining the results from all Cal/Val pairs provides probability distributions of the model coefficients and model errors. The method is generic and demonstrated using comprehensive matchup sets from two very different disciplines: soil moisture and water quality. The results demonstrate that the method provides robust model coefficients and quantitative measure of the model uncertainty. This approach can be adopted for the calibration/validation of satellite products of land and water surfaces, and the resulting uncertainty can be used as input to data assimilation schemes

Carbon and nitrogen cycling in the Scheldt estuary: the major players, long-term changes and an integrated view

The Scheldt estuary is a highly heterotrophic, nutrient-rich, turbid, tidal estuary in a densely populated area (Belgium/The Netherlands). Here we present the results (1) on the long-term changes in nutrient loadings and transformations within the estuary and (2) on nitrogen cycling rate measurements obtained with isotopic tracers. Moreover, we have developed and applied novel techniques that allow direct linking of process rates to the identity and biomass of the organisms involved. Monitoring data and process studies have been used in numerical models to integrate the various biogeochemical cycles and to advance our understanding of the evolving estuarine filter function of the Scheldt estuary