The size and polydispersity of silica nanoparticles under simulated hot spring conditions

The nucleation and growth of silica nanoparticles in supersaturated geothermal waters was simulated using a flow-through geothermal simulator system. The effect of silica concentration ([SiO2]), ionic strength (IS), temperature (T) and organic additives on the size and polydispersity of the forming silica nanoparticles was quantified. A decrease in temperature (58 to 33°C) and the addition of glucose restricted particle growth to sizes <20 nm, while varying [SiO2] or ISdid not affect the size (30-35 nm) and polydispersity (±9 nm) observed at 58°C. Conversely, the addition of xanthan gum induced the development of thin films that enhanced silica aggregation

The metagenomics of biosilicification: causes and effects

In order to determine the links between geochemical parameters controlling the formation of silica sinter in hot springs and their associated microbial diversity, a detailed characterisation of the waters and of in situ-grown silica sinters was combined with molecular phylogenetic analyses of the bacterial communities in Icelandic geothermal environments. At all but one site, the microorganisms clearly affected, and in part controlled, the formation of the macroscopic textures and structures of silica sinter edifices. In addition, the class and genera level phylogenetic diversity and distribution appeared to be closely linked to variations in temperature, salinity and pH regimes

The Biodiversity and Geochemistry of Cryoconite Holes in Queen Maud Land, East Antarctica

Cryoconite holes are oases of microbial diversity on ice surfaces. In contrast to the Arctic, where during the summer most cryoconite holes are ‘open’, in Continental Antarctica they are most often ‘lidded’ or completely frozen year-round. Thus, they represent ideal systems for the study of microbial community assemblies as well as carbon accumulation, since individual cryoconite holes can be isolated from external inputs for years. Here, we use high-throughput sequencing of the 16S and 18S rRNA genes to describe the bacterial and eukaryotic community compositions in cryoconite holes and surrounding lake, snow, soil and rock samples in Queen Maud Land. We cross correlate our findings with a broad range of geochemical data including for the first time 13C and 14C analyses of Antarctic cryoconites. We show that the geographic location has a larger effect on the distribution of the bacterial community compared to the eukaryotic community. Cryoconite holes are distinct from the local soils in both 13C and 14C and their isotopic composition is different from similar samples from the Arctic. Carbon contents were generally low (≤0.2%) and older (6–10 ky) than the surrounding soils, suggesting that the cryoconite holes are much more isolated from the atmosphere than the soils

Factors Controlling Structural and Floristic Variation of Riparian Zones in a Mountainous Landscape of the Western United States

We examined landscape patterns in the physical conditions and vegetative composition of montane riparian zones to identify their most important sources of variation. Information on plant species cover and on physical characteristics that occur at coarse, medium, and fine scales was collected for 144 riparian plots located throughout the Lake Tahoe Basin, which straddles the California-Nevada border in the western United States. Constrained and unconstrained ordination analyses were used to identify the most important correlates of physical form and plant species composition. Through multivariate analysis of environmental variables (principal components analysis), vegetation data (detrended correspondence analysis), and the combined relationship between the environmental and vegetation data (canonical correspondence analysis), we consistently found that the greatest variation occurred along a gradient of decreasing valley width, decreasing stream sinuosity, and increasing stream slope. Although surface characteristics reflected a 2nd important source of variation in physical conditions, plant species distribution was not strongly correlated with riparian surface conditions. Strong correlations among physical variables that occur at different scales, such as between valley form and geofluvial surface and between geofluvial surface and surface conditions, support the use of a physically based hierarchical framework for organizing riparian zones within the landscape. Such a hierarchical framework would be useful for interpreting patterns in riparian structure and process at different scales and could be applied to riparian zones in other mountain landscapes of the western United States and elsewhere. Moreover, our finding that riparian plant species composition is most strongly correlated with environmental variables that occur at coarse to moderate scales, most of which can be derived from existing data, supports the idea that modeling montane riparian community distribution using topographic and remotely sensed data could be useful; however, a large degree of species variation, unexplained by the variables we collected, indicates that other variables, perhaps disturbance regime, should be included in such a venture

Controlled biomineralization of magnetite (Fe₃O₄) by <i>Magnetospirillum gryphiswaldense</i>

Results from a study of the chemical composition and micro-structural characteristics of bacterial magnetosomes extracted from the magnetotactic bacterial strain Magnetospirillum gryphiswaldense are presented here. Using high-resolution transmission electron microscopy combined with selected-area electron diffraction and energy dispersive X-ray microanalysis, biogenic magnetite particles isolated from mature cultures were analysed for variations in crystallinity and particle size, as well as chain character and length. The analysed crystals showed a narrow size range (∼14-67 nm) with an average diameter of 46±6.8 nm, cuboctahedral morphologies and typical Gamma type crystal size distributions. The magnetite particles exhibited a high chemical purity (exclusively Fe3O4) and the majority fall within the single-magnetic-domain range

Crop and Couple: Cardiac Image Segmentation Using Interlinked Specialist Networks

Diagnosis of cardiovascular disease using automated methods often relies on the critical task of cardiac image segmentation. We propose a novel strategy that performs segmentation using specialist networks that focus on a single anatomy (left ventricle, right ventricle, or myocardium). Given an input long-axis cardiac MR image, our method performs a ternary segmentation in the first stage to identify these anatomical regions, followed by cropping the original image to focus subsequent processing on the anatomical regions. The specialist networks are coupled through an attention mechanism that performs cross-attention to interlink features from different anatomies, serving as a soft relative shape prior. Central to our approach is an additive attention block (E-2A block), which is used throughout our architecture thanks to its efficiency. The source code is available at1

Novel insights in cryptic diversity of snow and glacier ice algae communities combining 18S rRNA gene and ITS2 amplicon sequencing

Melting snow and glacier surfaces host microalgal blooms in polar and mountainous regions. The aim of this study was to determine the dominant taxa at the species level in the European Arctic and the Alps. A standardized protocol for amplicon metabarcoding using the 18S rRNA gene and ITS2 markers was developed. This is important because previous biodiversity studies have been hampered by the dominance of closely related algal taxa in snow and ice. Due to the limited resolution of partial 18S rRNA Illumina sequences, the hypervariable ITS2 region was used to further discriminate between the genotypes. Our results show that red snow was caused by the cosmopolitan Sanguina nivaloides (Chlamydomonadales, Chlorophyta) and two as of yet undescribed Sanguina species. Arctic orange snow was dominated by S. aurantia, which was not found in the Alps. On glaciers, at least three Ancylonema species (Zygnematales, Streptophyta) dominated. Golden-brown blooms consisted of Hydrurus spp. (Hydrurales, Stramenophiles) and these were mainly an Arctic phenomenon. For chrysophytes, only the 18S rRNA gene but not ITS2 sequences were amplified, showcasing how delicate the selection of eukaryotic ‘universal’ primers for community studies is and that primer specificity will affect diversity results dramatically. We propose our approach as a ‘best practice’

Ice sheets as a significant source of highly reactive nanoparticulate iron to the oceans

The Greenland and Antarctic Ice Sheets cover ~\n10% of global land surface, but are rarely considered as active components of the global iron cycle. The ocean waters around both ice sheets harbour highly productive coastal ecosystems, many of which are iron limited. Measurements of iron concentrations in subglacial runoff from a large Greenland Ice Sheet catchment reveal the potential for globally significant export of labile iron fractions to the near-coastal euphotic zone. We estimate that the flux of bioavailable iron associated with glacial runoff is 0.40–2.54?Tg per year in Greenland and 0.06–0.17?Tg per year in Antarctica. Iron fluxes are dominated by a highly reactive and potentially bioavailable nanoparticulate suspended sediment fraction, similar to that identified in Antarctic icebergs. Estimates of labile iron fluxes in meltwater are comparable with aeolian dust fluxes to the oceans surrounding Greenland and Antarctica, and are similarly expected to increase in a warming climate with enhanced melting

Learning filter functions in regularisers by minimising quotients

Learning approaches have recently become very popular in the field of inverse problems. A large variety of methods has been established in recent years, ranging from bi-level learning to high-dimensional machine learning techniques. Most learning approaches, however, only aim at fitting parametrised models to favourable training data whilst ignoring misfit training data completely. In this paper, we follow up on the idea of learning parametrised regularisation functions by quotient minimisation as established in [3]. We extend the model therein to include higher-dimensional filter functions to be learned and allow for fit- and misfit-training data consisting of multiple functions. We first present results resembling behaviour of well-established derivative-based sparse regularisers like total variation or higher-order total variation in one-dimension. Our second and main contribution is the introduction of novel families of non-derivative-based regularisers. This is accomplished by learning favourable scales and geometric properties while at the same time avoiding unfavourable ones

Long time series (1984–2020) of albedo variations on the Greenland ice sheet from harmonized Landsat and Sentinel 2 imagery

Albedo is a key factor in modulating the absorption of solar radiation on ice surfaces. Satellite measurements have shown a general reduction in albedo across the Greenland ice sheet over the past few decades, particularly along the western margin of the ice sheet, a region known as the Dark Zone (albedo < 0.45). Here we chose a combination of Landsat 4–8 and Sentinel 2 imagery to enable us to derive the longest record of albedo variations in the Dark Zone, running from 1984 to 2020. We developed a simple, pragmatic and efficient sensor transformation to provide a long time series of consistent, harmonized satellite imagery. Narrow to broadband conversion algorithms were developed from regression models of harmonized satellite data and in situ albedo from the Program for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather stations. The albedo derived from the harmonized Landsat and Sentinel 2 data shows that the maximum extent of the Dark Zone expanded rapidly between 2005 and 2007, increasing to ~280% of the average annual maximum extent of 2900 km2 to ~8000 km2 since. The Dark Zone is continuing to darken slowly, with the average annual minimum albedo decreasing at a rate of (p = 0.16, 2001–2020)