Soil Microbial Responses to Elevated CO2 and O3 in a Nitrogen-Aggrading Agroecosystem

Climate change factors such as elevated atmospheric carbon dioxide (CO2) and ozone (O3) can exert significant impacts on soil microbes and the ecosystem level processes they mediate. However, the underlying mechanisms by which soil microbes respond to these environmental changes remain poorly understood. The prevailing hypothesis, which states that CO2- or O3-induced changes in carbon (C) availability dominate microbial responses, is primarily based on results from nitrogen (N)-limiting forests and grasslands. It remains largely unexplored how soil microbes respond to elevated CO2 and O3 in N-rich or N-aggrading systems, which severely hinders our ability to predict the long-term soil C dynamics in agroecosystems. Using a long-term field study conducted in a no-till wheat-soybean rotation system with open-top chambers, we showed that elevated CO2 but not O3 had a potent influence on soil microbes. Elevated CO2 (1.5×ambient) significantly increased, while O3 (1.4×ambient) reduced, aboveground (and presumably belowground) plant residue C and N inputs to soil. However, only elevated CO2 significantly affected soil microbial biomass, activities (namely heterotrophic respiration) and community composition. The enhancement of microbial biomass and activities by elevated CO2 largely occurred in the third and fourth years of the experiment and coincided with increased soil N availability, likely due to CO2-stimulation of symbiotic N2 fixation in soybean. Fungal biomass and the fungi∶bacteria ratio decreased under both ambient and elevated CO2 by the third year and also coincided with increased soil N availability; but they were significantly higher under elevated than ambient CO2. These results suggest that more attention should be directed towards assessing the impact of N availability on microbial activities and decomposition in projections of soil organic C balance in N-rich systems under future CO2 scenarios

Topologically protected localised states in spin chains

We consider spin chain families inspired by the Su, Schrieffer and Hegger (SSH) model. We demonstrate explicitly the topologically induced spatial localisation of quantum states in our systems. We present detailed investigations of the effects of random noise, showing that these topologically protected states are very robust against this type of perturbation. Systems with such topological robustness are clearly good candidates for quantum information tasks and we discuss some potential applications. Thus, we present interesting spin chain models which show promising applications for quantum devices

mRNA localization, reaction centre biogenesis and thylakoid membrane targeting in cyanobacteria

The thylakoid membranes of cyanobacteria form a complex intracellular membrane system with a distinctive proteome. The sites of biogenesis of thylakoid proteins remain uncertain, as do the signals that direct thylakoid membrane-integral proteins to the thylakoids rather than to the plasma membrane. Here, we address these questions by using fluorescence in situ hybridization to probe the subcellular location of messenger RNA molecules encoding core subunits of the photosystems in two cyanobacterial species. These mRNAs cluster at thylakoid surfaces mainly adjacent to the central cytoplasm and the nucleoid, in contrast to mRNAs encoding proteins with other locations. Ribosome association influences the distribution of the photosynthetic mRNAs on the thylakoid surface, but thylakoid affinity is retained in the absence of ribosome association. However, thylakoid association is disrupted in a mutant lacking two mRNA-binding proteins, which probably play roles in targeting photosynthetic proteins to the thylakoid membrane

Fine root chemistry and decomposition in model communities of north-temperate tree species show little response to elevated atmospheric CO 2 and varying soil resource availability

Rising atmospheric [CO 2 ] has the potential to alter soil carbon (C) cycling by increasing the content of recalcitrant constituents in plant litter, thereby decreasing rates of decomposition. Because fine root turnover constitutes a large fraction of annual NPP, changes in fine root decomposition are especially important. These responses will likely be affected by soil resource availability and the life history characteristics of the dominant tree species. We evaluated the effects of elevated atmospheric [CO 2 ] and soil resource availability on the production and chemistry, mycorrhizal colonization, and decomposition of fine roots in an early- and late-successional tree species that are economically and ecologically important in north temperate forests. Open-top chambers were used to expose young trembling aspen ( Populus tremuloides ) and sugar maple ( Acer saccharum ) trees to ambient (36 Pa) and elevated (56 Pa) atmospheric CO 2 . Soil resource availability was composed of two treatments that bracketed the range found in the Upper Lake States, USA. After 2.5 years of growth, sugar maple had greater fine root standing crop due to relatively greater allocation to fine roots (30% of total root biomass) relative to aspen (7% total root biomass). Relative to the low soil resources treatment, aspen fine root biomass increased 76% with increased soil resource availability, but only under elevated [CO 2 ]. Sugar maple fine root biomass increased 26% with increased soil resource availability (relative to the low soil resources treatment), and showed little response to elevated [CO 2 ]. Concentrations of N and soluble phenolics, and C/N ratio in roots were similar for the two species, but aspen had slightly higher lignin and lower condensed tannins contents compared to sugar maple. As predicted by source-sink models of carbon allocation, pooled constituents (C/N ratio, soluble phenolics) increased in response to increased relative carbon availability (elevated [CO 2 ]/low soil resource availability), however, biosynthetically distinct compounds (lignin, starch, condensed tannins) did not always respond as predicted. We found that mycorrhizal colonization of fine roots was not strongly affected by atmospheric [CO 2 ] or soil resource availability, as indicated by root ergosterol contents. Overall, absolute changes in root chemical composition in response to increases in C and soil resource availability were small and had no effect on soil fungal biomass or specific rates of fine root decomposition. We conclude that root contributions to soil carbon cycling will mainly be influenced by fine root production and turnover responses to rising atmospheric [CO 2 ], rather than changes in substrate chemistry.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47710/1/442_2005_Article_191.pd

Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, , and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Search for resonant production of dark quarks in the dijet final state with the ATLAS detector

This paper presents a search for a new Z′ resonance decaying into a pair of dark quarks which hadronise into dark hadrons before promptly decaying back as Standard Model particles. This analysis is based on proton-proton collision data recorded at $$\sqrt{s}$$ s = 13 TeV with the ATLAS detector at the Large Hadron Collider between 2015 and 2018, corresponding to an integrated luminosity of 139 fb−1. After selecting events containing large-radius jets with high track multiplicity, the invariant mass distribution of the two highest-transverse-momentum jets is scanned to look for an excess above a data-driven estimate of the Standard Model multijet background. No significant excess of events is observed and the results are thus used to set 95% confidence-level upper limits on the production cross-section times branching ratio of the Z′ to dark quarks as a function of the Z′ mass for various dark-quark scenarios

Electron and photon energy calibration with the ATLAS detector using LHC Run 2 data

This paper presents the electron and photon energy calibration obtained with the ATLAS detector using 140 fb-1 of LHC proton-proton collision data recorded at √(s) = 13 TeV between 2015 and 2018. Methods for the measurement of electron and photon energies are outlined, along with the current knowledge of the passive material in front of the ATLAS electromagnetic calorimeter. The energy calibration steps are discussed in detail, with emphasis on the improvements introduced in this paper. The absolute energy scale is set using a large sample of Z-boson decays into electron-positron pairs, and its residual dependence on the electron energy is used for the first time to further constrain systematic uncertainties. The achieved calibration uncertainties are typically 0.05% for electrons from resonant Z-boson decays, 0.4% at ET ∼ 10 GeV, and 0.3% at ET ∼ 1 TeV; for photons at ET ∼ 60 GeV, they are 0.2% on average. This is more than twice as precise as the previous calibration. The new energy calibration is validated using J/ψ → ee and radiative Z-boson decays

Accuracy versus precision in boosted top tagging with the ATLAS detector

Abstract The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.</jats:p