Understanding Structure and Function in Semiarid Ecosystems: Implications for Terrestrial Carbon Dynamics in Drylands

This study advances understanding of how the changes in ecosystem structure and function associated with woody shrub encroachment in semi-arid grasslands alter ecosystem carbon (C) dynamics. In terms of both magnitude and dynamism, dryland ecosystems represent a major component of the global C cycle. Woody shrub encroachment is a widespread phenomenon globally, which is known to substantially alter ecosystem structure and function, with resultant impacts on C dynamics. A series of focal sites were studied at the Sevilleta National Wildlife Refuge in central New Mexico, USA. A space-for-time analogue was used to identify how landscape structure and function change at four stages over a grassland to shrubland transition. The research had three key threads: 1. Soil-associated carbon: Stocks of organic and inorganic C in the near-surface soil, and the redistribution of these C stocks by erosion during high-intensity rainfall events were quantified using hillslope-scale monitoring plots. Coarse (>2 mm) clasts were found to account for a substantial proportion of the organic and inorganic C in these calcareous soils, and the erosional effluxes of both inorganic and organic C increased substantially across the vegetation ecotone. Eroded sediment was found to be significantly enriched in organic C relative to the contributing soil with systematic changes in OC enrichment across the vegetation transition. The OC enrichment dynamics observed were inconsistent with existing understanding (derived largely from reductionist, laboratory-based experiments) that OC enrichment is largely insignificant in the erosional redistribution of C. 2. Plant biomass: Cutting-edge proximal remote sensing approaches, using a remotely piloted lightweight multirotor drone combined with structure-from-motion (SfM) photogrammetry were developed and used to quantify biomass carbon stocks at the focal field sites. In such spatially heterogeneous and temporally dynamic ecosystems existing measurement techniques (e.g. on-the-ground observations or satellite- or aircraft-based remote sensing) struggle to capture the complexity of fine-grained vegetation structure, which is crucial for accurately estimating biomass. The data products available from the novel SfM approach developed for this research quantified plants just 15 mm high, achieving a fidelity nearly two orders of magnitude finer than previous implementations of the method. The approach developed here will revolutionise the study of biomass dynamics in short-sward ecogeomorphic systems. 3. Ecohydrological modelling: Understanding the effects of water-mediated degradation processes on ecosystem carbon dynamics over greater than observable spatio-temporal scales is complicated by significant scale-dependencies and thus requires detailed mechanistic understanding. A process-based, spatially-explicit ecohydrological modelling approach (MAHLERAN - Model for Assessing Hillslope to Landscape Erosion, Runoff and Nutrients) was therefore comprehensively evaluated against a large assemblage of rainfall runoff events. This evaluation highlighted both areas of strength in the current model structure, and also areas of weakness for further development. The research has improved understanding of ecosystem degradation processes in semi-arid rangelands, and demonstrates that woody shrub encroachment may lead to a long-term reduction in ecosystem C storage, which is contrary to the widely promulgated view that woody shrub encroachment increases C storage in terrestrial ecosystems.NERC Doctoral Training Grant (NE/K500902/1)NSF Long Term Ecological Research Program at the Sevilleta National Wildlife Refuge (DEB-1232294

A Call for a Better Understanding of Aquatic Chytrid Biology

The phylum Chytridiomycota (the “chytrids”) is an early-diverging, mostly unicellular, lineage of fungi that consists of significant aquatic saprotrophs, parasites, and pathogens, and is of evolutionary interest because its members retain biological traits considered ancestral in the fungal kingdom. While the existence of aquatic chytrids has long been known, their fundamental biology has received relatively little attention. We are beginning to establish a detailed understanding of aquatic chytrid diversity and insights into their ecological functions and prominence. However, the underpinning biology governing their aquatic ecological activities and associated core processes remain largely understudied and therefore unresolved. Many biological questions are outstanding for aquatic chytrids. What are the mechanisms that control their development and life cycle? Which core processes underpin their aquatic influence? What can their biology tell us about the evolution of fungi and the wider eukaryotic tree of life? We propose that the field of aquatic chytrid ecology could be further advanced through the improved understanding of chytrid biology, including the development of model aquatic chytrids and targeted studies using culture-independent approaches.</jats:p

Bacterial Community Composition in the Sea Surface Microlayer Off the Peruvian Coast

The sea surface microlayer (SML) is located at the air-sea interface, with microorganisms and organic matter in the SML influencing air-sea exchange processes. Yet understanding of the SML bacterial (bacterioneuston) community composition and assembly remains limited. Availability of organic matter, UV radiation and wind speed have previously been suggested to influence the community composition of bacterioneuston. Another mechanism potentially controlling bacterioneuston dynamics is bacterioplankton attached to gel-like particles that ascend through the water column into the SML. We analyzed the bacterial community composition, Transparent Exopolymer Particles (TEP) abundance and nutrient concentrations in the surface waters of the Peruvian upwelling region. The bacterioneuston and bacterioplankton communities were similar, suggesting a close spatial coupling. Four Bacteroidetes families were significantly enriched in the SML, two of them, the Flavobacteriaceae and Cryomorphaceae, were found to comprise the majority of SML-enriched operational taxonomic units (OTUs). The enrichment of these families was controlled by a variety of environmental factors. The SML-enriched bacterial families were negatively correlated with water temperature and wind speed in the SML and positively correlated with nutrient concentrations, salinity and TEP in the underlying water (ULW). The correlations with nutrient concentrations and salinity suggest that the enriched bacterial families were more abundant at the upwelling stations

Comparison of bacterioneuston and bacterioplankton dynamics during a phytoplankton bloom in a fjord mesocosm

The bacterioneuston is the community of Bacteria present in surface microlayers, the thin surface film that forms the interface between aquatic environments and the atmosphere. In this study we compared bacterial cell abundance and bacterial community structure of the bacterioneuston and the bacterioplankton (from the subsurface water column) during a phytoplankton bloom mesocosm experiment. Bacterial cell abundance, determined by flow cytometry, followed a typical bacterioplankton response to a phytoplankton bloom, with Synechococcus and high nucleic acid (HNA) bacterial cell numbers initially falling, probably due to selective protist grazing. Subsequently HNA and low nucleic acid (LNA) bacterial cells increased in abundance but Synechococcus did not. There was no significant difference between bacterioneuston and bacterioplankton cell abundances during the experiment. Conversely, distinct and consistent differences between the bacterioneuston and the bacterioplankton community structure were observed. This was monitored simultaneously by Bacteria 16S rRNA gene terminal restriction fragment length polymorphism (T-RFLP) and denaturing gradient gel electrophoresis (DGGE). The conserved patterns of community structure observed in all of the mesocosms indicate that the bacterioneuston is distinctive and non-random

Chytrid rhizoid morphogenesis resembles hyphal development in multicellular fungi and is adaptive to resource availability

Key to the ecological prominence of fungi is their distinctive cell biology, our understanding of which has been principally based on dikaryan hyphal and yeast forms. The early-diverging Chytridiomycota (chytrids) are ecologically important and a significant component of fungal diversity, yet their cell biology remains poorly understood. Unlike dikaryan hyphae, chytrids typically attach to substrates and feed osmotrophically via anucleate rhizoids. The evolution of fungal hyphae appears to have occurred from rhizoid-bearing lineages and it has been hypothesized that a rhizoid-like structure was the precursor to multicellular hyphae. Here, we show in a unicellular chytrid, Rhizoclosmatium globosum, that rhizoid development exhibits striking similarities with dikaryan hyphae and is adaptive to resource availability. Rhizoid morphogenesis exhibits analogous patterns to hyphal growth and is controlled by β-glucan-dependent cell wall synthesis and actin polymerization. Chytrid rhizoids growing from individual cells also demonstrate adaptive morphological plasticity in response to resource availability, developing a searching phenotype when carbon starved and spatial differentiation when interacting with particulate organic matter. We demonstrate that the adaptive cell biology and associated developmental plasticity considered characteristic of hyphal fungi are shared more widely across the Kingdom Fungi and therefore could be conserved from their most recent common ancestor

Context-specific gene regulatory networks subdivide intrinsic subtypes of breast cancer

<p>Abstract</p> <p>Background</p> <p>Breast cancer is a highly heterogeneous disease with respect to molecular alterations and cellular composition making therapeutic and clinical outcome unpredictable. This diversity creates a significant challenge in developing tumor classifications that are clinically reliable with respect to prognosis prediction.</p> <p>Results</p> <p>This paper describes an unsupervised context analysis to infer context-specific gene regulatory networks from 1,614 samples obtained from publicly available gene expression data, an extension of a previously published methodology. We use the context-specific gene regulatory networks to classify the tumors into clinically relevant subgroups, and provide candidates for a finer sub-grouping of the previously known intrinsic tumors with a focus on Basal-like tumors. Our analysis of pathway enrichment in the key contexts provides an insight into the biological mechanism underlying the identified subtypes of breast cancer.</p> <p>Conclusions</p> <p>The use of context-specific gene regulatory networks to identify biological contexts from heterogenous breast cancer data set was able to identify genomic drivers for subgroups within the previously reported intrinsic subtypes. These subgroups (contexts) uphold the clinical relevant features for the intrinsic subtypes and were associated with increased survival differences compared to the intrinsic subtypes. We believe our computational approach led to the generation of novel rationalized hypotheses to explain mechanisms of disease progression within sub-contexts of breast cancer that could be therapeutically exploited once validated.</p

Latitudinal variation in the potential activity of Atlantic Ocean bacterioplankton revealed through 16S rRNA and 16S rRNA gene metabarcoding

The activities of bacterioplankton sustain open ocean biogeochemical and ecological processes, however, little is known about the activity of specific bacterioplankton, especially related to their biogeography across oceanic scales. The Atlantic is the second largest of the world’s oceans and has an essential role in the global carbon cycle. Here, we show congruence in the structure of 16S rRNA and 16S rRNA gene derived bacterioplankton communities throughout the Atlantic Ocean from temperate to tropical regions. We used 16S rRNA:16S rRNA gene ratios as a phylogenetically resolved proxy for potential activity, demonstrating ocean-scale patterns of putative oligotrophy and copiotrophy in major bacterioplankton groups, with spatial niche partitioning being evident at single-nucleotide resolution within some groups, including the Flavobacteria and SAR86. This study examines the potential structure of the active microbiome of the Atlantic Ocean, providing novel insights into the ecology and life history strategies of both well-known and currently understudied bacterioplankton taxa

Endangered Archaeology in the Middle East and North Africa: Introducing the EAMENA Project

This project uses satellite imagery and historic aerial photographs to discover and interpret archaeological sites. It has created an open access database of archaeological records that provides basic information so that the sites can be better under- stood and preserved in the future. The threats to sites in the Middle East and North Africa are increasing and creating a record of previously unrecorded sites using this methodology may be our the last chance before they are destroyed

Endangered Archaeology in the Middle East and North Africa: Introducing the EAMENA Project

This project uses satellite imagery and historic aerial photographs to discover and interpret archaeological sites. It has created an open access database of archaeological records that provides basic information so that the sites can be better under- stood and preserved in the future. The threats to sites in the Middle East and North Africa are increasing and creating a record of previously unrecorded sites using this methodology may be our the last chance before they are destroyed

The Full Event Interpretation -- An exclusive tagging algorithm for the Belle II experiment

The Full Event Interpretation is presented: a new exclusive tagging algorithm used by the high-energy physics experiment Belle II. The experimental setup of Belle II allows the precise measurement of otherwise inaccessible $B$ meson decay-modes. The Full Event Interpretation algorithm enables many of these measurements. The algorithm relies on machine learning to automatically identify plausible $B$ meson decay chains based on the data recorded by the detector. Compared to similar algorithms employed by previous experiments, the Full Event Interpretation provides a greater efficiency, yielding a larger effective sample size usable in the measurement.Comment: 11 pages, 7 figures, 1 tabl