Restoration of eucalypt grassy woodland: effects of experimental interventions on ground-layer vegetation

We report on the effects of broad-scale restoration treatments on the ground layer of eucalypt grassy woodland in south-eastern Australia. The experiment was conducted in two conservation reserves from which livestock grazing had previously been removed. Changes in biomass, species diversity, ground-cover attributes and life-form were analysed over a 4-year period in relation to the following experimental interventions: (1) reduced kangaroo density, (2) addition of coarse woody debris and (3) fire (a single burn). Reducing kangaroo density doubled total biomass in one reserve, but no effects on exotic biomass, species counts or ground cover attributes were observed. Coarse woody debris also promoted biomass, particularly exotic annual forbs, as well as plant diversity in one of the reserves. The single burn reduced biomass, but changed little else. Overall, we found the main driver of change to be the favourable growth seasons that had followed a period of drought. This resulted in biomass increasing by 67%, (mostly owing to the growth of perennial native grasses), whereas overall native species counts increased by 18%, and exotic species declined by 20% over the 4-year observation period. Strategic management of grazing pressure, use of fire where biomass has accumulated and placement of coarse woody debris in areas of persistent erosion will contribute to improvements in soil and vegetation condition, and gains in biodiversity, in the future.Funding and in-kind logistic support for this project was provided by the ACT Government as part of an Australian Research Council Linkage Grant (LP0561817; LP110100126). Drafts of the manuscript were read by Saul Cunningham and Ben Macdonald

Quantifying methane and nitrous oxide emissions from the UK and Ireland using a national-scale monitoring network

The UK is one of several countries around the world that has enacted legislation to reduce its greenhouse gas emissions. In this study, we present top-down emissions of methane (CH4) and nitrous oxide (N2O) for the UK and Ireland over the period August 2012 to August 2014. These emissions were inferred using measurements from a network of four sites around the two countries. We used a hierarchical Bayesian inverse framework to infer fluxes as well as a set of covariance parameters that describe uncertainties in the system. We inferred average UK total emissions of 2.09 (1.65–2.67) Tg yr−1 CH4 and 0.101 (0.068–0.150) Tg yr−1 N2O and found our derived UK estimates to be generally lower than the a priori emissions, which consisted primarily of anthropogenic sources and with a smaller contribution from natural sources. We used sectoral distributions from the UK National Atmospheric Emissions Inventory (NAEI) to determine whether these discrepancies can be attributed to specific source sectors. Because of the distinct distributions of the two dominant CH4 emissions sectors in the UK, agriculture and waste, we found that the inventory may be overestimated in agricultural CH4 emissions. We found that annual mean N2O emissions were consistent with both the prior and the anthropogenic inventory but we derived a significant seasonal cycle in emissions. This seasonality is likely due to seasonality in fertilizer application and in environmental drivers such as temperature and rainfall, which are not reflected in the annual resolution inventory. Through the hierarchical Bayesian inverse framework, we quantified uncertainty covariance parameters and emphasized their importance for high-resolution emissions estimation. We inferred average model errors of approximately 20 and 0.4 ppb and correlation timescales of 1.0 (0.72–1.43) and 2.6 (1.9–20 3.9) days for CH4 and N2O, respectively. These errors are a combination of transport model errors as well as errors due to unresolved emissions processes in the inventory. We found the largest CH4 errors at the Tacolneston station in eastern England, which may be due to sporadic emissions from landfills and offshore gas in the North Sea

Association between genotypic diversity and biofilm production in group B Streptococcus

Background: Group B Streptococcus (GBS) is a leading cause of sepsis and meningitis and an important factor in premature and stillbirths. Biofilm production has been suggested to be important for GBS pathogenesis alongside many other elements, including phylogenetic lineage and virulence factors, such as pili and capsule type. A complete understanding of the confluence of these components, however, is lacking. To identify associations between biofilm phenotype, pilus profile and lineage, 293 strains from asymptomatic carriers, invasive disease cases, and bovine mastitis cases, were assessed for biofilm production using an in vitro assay. Results: Multilocus sequence type (ST) profile, pilus island profile, and isolate source were associated with biofilm production. Strains from invasive disease cases and/or belonging to the ST-17 and ST-19 lineages were significantly more likely to form weak biofilms, whereas strains producing strong biofilms were recovered more frequently from individuals with asymptomatic colonization. Conclusions: These data suggest that biofilm production is a lineage-specific trait in GBS and may promote colonization of strains representing lineages other than STs 17 and 19. The findings herein also demonstrate that biofilms must be considered in the treatment of pregnant women, particularly for women with heavy GBS colonization

Exploratory Analysis of Highly Heterogeneous Document Collections

We present an effective multifaceted system for exploratory analysis of highly heterogeneous document collections. Our system is based on intelligently tagging individual documents in a purely automated fashion and exploiting these tags in a powerful faceted browsing framework. Tagging strategies employed include both unsupervised and supervised approaches based on machine learning and natural language processing. As one of our key tagging strategies, we introduce the KERA algorithm (Keyword Extraction for Reports and Articles). KERA extracts topic-representative terms from individual documents in a purely unsupervised fashion and is revealed to be significantly more effective than state-of-the-art methods. Finally, we evaluate our system in its ability to help users locate documents pertaining to military critical technologies buried deep in a large heterogeneous sea of information.Comment: 9 pages; KDD 2013: 19th ACM SIGKDD Conference on Knowledge Discovery and Data Minin

A five year record of high-frequency in situ measurements of non-methane hydrocarbons at Mace Head, Ireland

Continuous high-frequency in situ measurements of a range of non-methane hydrocarbons have been made at Mace Head since January 2005. Mace Head is a background Northern Hemispheric site situated on the eastern edge of the Atlantic. Five year measurements (2005–2009) of six C<sub>2</sub>–C<sub>5</sub> non-methane hydrocarbons have been separated into baseline Northern Hemispheric and European polluted air masses, among other sectors. Seasonal cycles in baseline Northern Hemispheric air masses and European polluted air masses arriving at Mace Head have been studied. Baseline air masses show a broad summer minima between June and September for shorter lived species, longer lived species show summer minima in July/August. All species displayed a winter maxima in February. European air masses showed baseline elevated mole fractions for all non-methane hydrocarbons. Largest elevations (of up to 360 ppt for ethane maxima) from baseline data were observed in winter maxima, with smaller elevations observed during the summer. Analysis of temporal trends using the Mann-Kendall test showed small (<6 % yr<sup>−1</sup>) but statistically significant decreases in the butanes and <i>i</i>-pentane between 2005 and 2009 in European air. No significant trends were found for any species in baseline air