Modelling the effect of vertical mixing on bottle incubations for determining in situ phytoplankton dynamics. II. Primary production

The estimation of in situ phytoplankton primary production is pivotal to many questions in biological oceanography and marine ecology both in a local and global context. Applications range from earth system modelling, the characterisation of aquatic ecosystem dynamics, or the local management of water quality. A common approach for estimating in situ primary production is to incubate natural phytoplankton assemblages in clear bottles at a range of fixed depths and to measure the uptake of carbon (14C) during the incubation period (typically 24 h). One of the main concerns with using fixed-depth bottle incubations is whether stranding samples at fixed depths biases the measured CO2 fixation relative to the 'true' in situ mixed conditions. Here we employ an individual based turbulence and photosynthesis model, which also accounts for photoacclimation and -inhibition, to examine whether the in vitro productivity estimates obtained from fixed-depth incubations are representative of the in situ productivity in a freely mixing water column. While previous work suggested that in vitro estimates could either over- or underestimate the in situ productivity, we show that the errors due to arresting the incubation bottles at fixed depths are indeed minimal. We present possible explanations for how previous authors could have arrived at contradictory results and discuss whether they might be artefacts related to the particular sampling protocol used. We discuss the errors associated with chlorophyll-based incubation methods for determining in situ phytoplankton growth rates in Ross et al. (2011; Mar Ecol Prog Ser 435:13-31). © Inter-Research 2011

Modelling the effect of vertical mixing on bottle incubations for determining in situ phytoplankton dynamics. I. Growth rates

Reliable estimates of in situ phytoplankton growth rates are central to understanding the dynamics of aquatic ecosystems. A common approach for estimating in situ growth rates is to incubate natural phytoplankton assemblages in clear bottles at fixed depths or irradiance levels and measure the change in chlorophyll a (Chl) over the incubation period (typically 24 h). Using a modelling approach, we investigate the accuracy of these Chl-based methods focussing on 2 aspects: (1) in a freely mixing surface layer, the cells are typically not in balanced growth, and with photoacclimation, changes in Chl may yield different growth rates than changes in carbon; and (2) the in vitro methods neglect any vertical movement due to turbulence and its effect on the cells' light history. The growth rates thus strongly depend on the incubation depth and are not necessarily representative of the depth-integrated in situ growth rate in the freely mixing surface layer. We employ an individual based turbulence and photosynthesis model, which also accounts for photoacclimation and photo - inhibition, to show that the in vitro Chl-based growth rate can differ both from its carbon-based in vitro equivalent and from the in situ value by up to 100%, depending on turbulence intensity, optical depth of the mixing layer, and incubation depth within the layer. We make recommendations for choosing the best depth for single-depth incubations. Furthermore we demonstrate that, if incubation bottles are being oscillated up and down through the water column, these systematic errors can be significantly reduced. In the present study, we focus on Chl-based methods only, while productivity measurements using carbon-based techniques (e.g. 14C) are discussed in Ross et al. (2011; Mar Ecol Prog Ser 435:33-45). © Inter-Research 2011

Representing sensorml and O&M files in android clients

Peer Reviewe

Estimating underwater light diffuse attenuation with low-cost devices: optimal sensor configuration analysis using radiative transfer models

Peer Reviewe

Cellular self-organization on micro-structured surfaces

Micro-patterned surfaces are frequently used in high-throughput single-cell studies, as they allow one to image isolated cells in defined geometries. Commonly, cells are seeded in excess onto the entire chip, and non-adherent cells are removed from the unpatterned sectors by rinsing. Here, we report on the phenomenon of cellular self-organization, which allows for autonomous positioning of cells on micro-patterned surfaces over time. We prepared substrates with a regular lattice of protein-coated adhesion sites surrounded by PLL-g-PEG passivated areas, and studied the time course of cell ordering. After seeding, cells randomly migrate over the passivated surface until they find and permanently attach to adhesion sites. Efficient cellular self-organization was observed for three commonly used cell lines (HuH7, A549, and MDA-MB-436), with occupancy levels typically reaching 40-60% after 3-5 h. The time required for sorting was found to increase with increasing distance between adhesion sites, and is well described by the time-to-capture in a random-search model. Our approach thus paves the way for automated filling of cell arrays, enabling high-throughput single-cell analysis of cell samples without losses