Decline in Coccolithophore Diversity and Impact on Coccolith Morphogenesis Along a Natural CO2 Gradient

A natural pH gradient caused by marine CO2 seeps off Vulcano Island (Italy) was used to assess the effects of ocean acidification on coccolithophores, which are abundant planktonic unicellular calcifiers. Such seeps are used as natural laboratories to study the effects of ocean acidification on marine ecosystems, since they cause long-term changes in seawater carbonate chemistry and pH, exposing the organisms to elevated CO2 concentrations and therefore mimicking future scenarios. Previous work at CO2 seeps has focused exclusively on benthic organisms. Here we show progressive depletion of 27 coccolithophore species, in terms of cell concentrations and diversity, along a calcite saturation gradient from Omega calcite 6.4 to <1. Water collected close to the main CO2 seeps had the highest concentrations of malformed Emiliania huxleyi. These observations add to a growing body of evidence that ocean acidification may benefit some algae but will likely cause marine biodiversity loss, especially by impacting calcifying species, which are affected as carbonate saturation falls.

Plant height along the plant diversity gradient in the Jena Experiment (Main Experiment, year 2007)

This data set contains measurements of plant height: vegetative height (heighest leaf) and regenerative height (heighest flower) in 2007 from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the Main Experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2007, plant height was recorded twice a year just before biomass harvest (during peak standing biomass in late May and in late August). For target plant individuals at 10 points separated by 1 m each along a transect in the central area in the plots, vegetative height (heighest leaf) and regenerative height (heighest flower) were measured as standing height (without stretching the plant). In 2007, also the plots of the management experiment, that altered mowing frequency and fertilized subplots (see further details below) were sampled by measuring vegatation height five times, every 0.5m on a 3m transekt along the side of the management plots. Provided are the individual measurements and the mean over the measured plants.

Plant height along the plant diversity gradient in the Jena Experiment (Main Experiment, year 2008)

This data set contains measurements of plant height: vegetative height (heighest leaf) and regenerative height (heighest flower) in 2008 from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the Main Experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2008, plant height was recorded twice a year just before biomass harvest (during peak standing biomass in late May and in late August). For target plant individuals at 10 points separated by 1 m each along a transect in the central area in the plots, vegetative height (heighest leaf) and regenerative height (heighest flower) were measured as standing height (without stretching the plant). In 2008, also the plots of the management experiment, that altered mowing frequency and fertilized subplots (see further details below) were sampled by measuring vegatation height five times, every 1m on a 5m transekt along the side of the management plots. Provided are the individual measurements and the mean over the measured plants.

Plant height along the plant diversity gradient in the Jena Experiment (Main Experiment, year 2005)

This data set contains measurements of plant height: vegetative height (heighest leaf) and regenerative height (heighest flower) in 2005 from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the Main Experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2005, plant height was recorded twice a year just before biomass harvest (during peak standing biomass in late May and in late August). For target plant individuals at 10 points separated by 1 m each along a transect in the central area in the plots, vegetative height (heighest leaf) and regenerative height (heighest flower) were measured as standing height (without stretching the plant). Provided are the individual measurements and the mean over the measured plants.

Plant height along the plant diversity gradient in the Jena Experiment (Main Experiment, year 2006)

This data set contains measurements of plant height: vegetative height (heighest leaf) and regenerative height (heighest flower) in 2006 from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the Main Experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2006, plant height was recorded twice a year just before biomass harvest (during peak standing biomass in late May and in late August). For target plant individuals at 10 points separated by 1 m each along a transect in the central area in the plots, vegetative height (heighest leaf) and regenerative height (heighest flower) were measured as standing height (without stretching the plant). In 2006, also the plots of the management experiment, that altered mowing frequency and fertilized subplots (see further details below) were sampled by measuring vegatation height five times, every 1m on a 5m transekt along the side of the management plots. Provided are the individual measurements and the mean over the measured plants.

Shallow water marine sediment bacterial community shifts along a natural CO2 gradient in the Mediterranean Sea Off vulcano, Italy

The effects of increasing atmospheric CO(2) on ocean ecosystems are a major environmental concern, as rapid shoaling of the carbonate saturation horizon is exposing vast areas of marine sediments to corrosive waters worldwide. Natural CO(2) gradients off Vulcano, Italy, have revealed profound ecosystem changes along rocky shore habitats as carbonate saturation levels decrease, but no investigations have yet been made of the sedimentary habitat. Here, we sampled the upper 2 cm of volcanic sand in three zones, ambient (median pCO(2) 419 µatm, minimum Omega (arag) 3.77), moderately CO(2)-enriched (median pCO(2) 592 µatm, minimum Omega (arag) 2.96), and highly CO(2)-enriched (median pCO(2) 1611 µatm, minimum Omega (arag) 0.35). We tested the hypothesis that increasing levels of seawater pCO(2) would cause significant shifts in sediment bacterial community composition, as shown recently in epilithic biofilms at the study site. In this study, 454 pyrosequencing of the V1 to V3 region of the 16S rRNA gene revealed a shift in community composition with increasing pCO(2). The relative abundances of most of the dominant genera were unaffected by the pCO(2) gradient, although there were significant differences for some 5 % of the genera present (viz. Georgenia, Lutibacter, Photobacterium, Acinetobacter, and Paenibacillus), and Shannon Diversity was greatest in sediments subject to long-term acidification (>100 years). Overall, this supports the view that globally increased ocean pCO(2) will be associated with changes in sediment bacterial community composition but that most of these organisms are resilient. However, further work is required to assess whether these results apply to other types of coastal sediments and whether the changes in relative abundance of bacterial taxa that we observed can significantly alter the biogeochemical functions of marine sediments.

A parallel implementation of 3D Zernike moment analysis

Zernike polynomials are a well known set of functions that find many applications in image or pattern characterization because they allow to construct shape descriptors that are invariant against translations, rotations or scale changes. The concepts behind them can be extended to higher dimension spaces, making them also fit to describe volumetric data. They have been less used than their properties might suggest due to their high computational cost. We present a parallel implementation of 3D Zernike moments analysis, written in C with CUDA extensions, which makes it practical to employ Zernike descriptors in interactive applications, yielding a performance of several frames per second in voxel datasets about 2003 in size. In our contribution, we describe the challenges of implementing 3D Zernike analysis in a general-purpose GPU. These include how to deal with numerical inaccuracies, due to the high precision demands of the algorithm, or how to deal with the high volume of input data so that it does not become a bottleneck for the system.

Probabilistic Atlas Based Segmentation Using Affine Moment Descriptors and Graph-Cuts

We show a procedure for constructing a probabilistic atlas based on affine moment descriptors. It uses a normalization procedure over the labeled atlas. The proposed linear registration is defined by closed-form expressions involving only geometric moments. This procedure applies both to atlas construction as atlas-based segmentation. We model the likelihood term for each voxel and each label using parametric or nonparametric distributions and the prior term is determined by applying the vote-rule. The probabilistic atlas is built with the variability of our linear registration. We have two segmentation strategy: a) it applies the proposed affine registration to bring the target image into the coordinate frame of the atlas or b) the probabilistic atlas is non-rigidly aligning with the target image, where the probabilistic atlas is previously aligned to the target image with our affine registration. Finally, we adopt a graph cut - Bayesian framework for implementing the atlas-based segmentation.

Level Set Segmentation with Shape and Appearance Models Using Affine Moment Descriptors

We propose a level set based variational approach that incorporates shape priors into edge-based and region-based models. The evolution of the active contour depends on local and global information. It has been implemented using an efficient narrow band technique. For each boundary pixel we calculate its dynamic according to its gray level, the neighborhood and geometric properties established by training shapes. We also propose a criterion for shape aligning based on affine transformation using an image normalization procedure. Finally, we illustrate the benefits of the our approach on the liver segmentation from CT images.

LHPP, the light-harvesting NADPH:protochlorophyllide (Pchlide) oxido¬reductase:Pchlide complex of etiolated plants, is developmentally expressed across the barley leaf gradient

NADPH:protochlorophyllide oxidoreductase is a key enzyme for the light-induced greening of etiolated angiosperm plants. In barley, two POR proteins exist termed PORA and PORB that have previously been proposed to structurally and functionally cooperate in terms of a higher molecular mass light-harvesting complex named LHPP, in the prolamellar body of etioplasts [Nature 397 (1999) 80]. In this study we examined the expression pattern of LHPP during seedling etiolation and de-etiolation under different experimental conditions. Our results show that LHPP is developmentally expressed across the barley leaf gradient. We further provide evidence that LHPP operates both in plants that etiolate completely before being exposed to white light and in plants that etiolate only partially and begin light-harvesting as soon as traces of light become available in the uppermost parts of the soil. As a result of light absorption, in either case LHPP converts Pchlide a to chlorophyllide (Chlide) a and in turn disintegrates. The released Chlide a, as well as Chlide b produced upon LHPP’s light-dependent dissociation, which leads to the activation of the PORA as a Pchlide b-reducing enzyme, then bind to homologs of water-soluble chlorophyll proteins of Brassicaceae. We propose that these proteins transfer Chlide a and Chlide b to the thylakoids, where their esterification with phytol and assembly into the photosynthetic membrane complexes ultimately takes place. Presumably due to the tight coupling of LHPP synthesis and degradation, as well as WSCP formation and photosynthetic membrane assembly, efficient photo-protection is conferred onto the plant.

Hybrid topological derivative and gradient-based methods for electrical impedance tomography

We present a technique to reconstruct the electromagnetic properties of a medium or a set of objects buried inside it from boundary measurements when applying electric currents through a set of electrodes. The electromagnetic parameters may be recovered by means of a gradient method without a priori information on the background. The shape, location and size of objects, when present, are determined by a topological derivative-based iterative procedure. The combination of both strategies allows improved reconstructions of the objects and their properties, assuming a known background.

Diffusion Gradient Temporal Difference for Cooperative Reinforcement Learning with Linear Function Approximation

We introduce a diffusion-based algorithm in which multiple agents cooperate to predict a common and global statevalue function by sharing local estimates and local gradient information among neighbors. Our algorithm is a fully distributed implementation of the gradient temporal difference with linear function approximation, to make it applicable to multiagent settings. Simulations illustrate the benefit of cooperation in learning, as made possible by the proposed algorithm.

Design of spherical symmetric gradient index lenses

Spherical symmetric refractive index distributions also known as Gradient Index lenses such as the Maxwell-Fish-Eye (MFE), the Luneburg or the Eaton lenses have always played an important role in Optics. The recent development of the technique called Transformation Optics has renewed the interest in these gradient index lenses. For instance, Perfect Imaging within the Wave Optics framework has recently been proved using the MFE distribution. We review here the design problem of these lenses, classify them in two groups (Luneburg moveable-limits and fixed-limits type), and establish a new design techniques for each type of problem.