Recent Shift in Climate Relationship Enables Prediction of the Timing of Bird Breeding

Large-scale climate processes influence many aspects of ecology including breeding phenology, reproductive success and survival across a wide range of taxa. Some effects are direct, for example, in temperate-zone birds, ambient temperature is an important cue enabling breeding effort to coincide with maximum food availability, and earlier breeding in response to warmer springs has been documented in many species. In other cases, time-lags of up to several years in ecological responses have been reported, with effects mediated through biotic mechanisms such as growth rates or abundance of food supplies. Here we use 23 years of data for a temperate woodland bird species, the great tit (Parus major), breeding in deciduous woodland in eastern England to demonstrate a time-lagged linear relationship between the on-set of egg laying and the winter index of the North Atlantic Oscillation such that timing can be predicted from the winter index for the previous year. Thus the timing of bird breeding (and, by inference, the timing of spring events in general) can be predicted one year in advance. We also show that the relationship with the winter index appears to arise through an abiotic time-lag with local spring warmth in our study area. Examining this link between local conditions and larger-scale processes in the longer-term showed that, in the past, significant relationships with the immediately preceding winter index were more common than those with the time-lagged index, and especially so from the late 1930s to the early 1970s. However, from the mid 1970s onwards, the time-lagged relationship has become the most significant, suggesting a recent change in climate patterns. The strength of the current time-lagged relationship suggests that it might have relevance for other temperature-dependent ecological relationships

Neurodevelopmental toxicity of prenatal polychlorinated biphenyls (PCBs) by chemical structure and activity: a birth cohort study

Abstract Background Polychlorinated biphenyls (PCBs) are ubiquitous environmental toxins. Although there is growing evidence to support an association between PCBs and deficits of neurodevelopment, the specific mechanisms are not well understood. The potentially different roles of specific PCB groups defined by chemical structures or hormonal activities e.g., dioxin-like, non-dioxin like, or anti-estrogenic PCBs, remain unclear. Our objective was to examine the association between prenatal exposure to defined subsets of PCBs and neurodevelopment in a cohort of infants in eastern Slovakia enrolled at birth in 2002-2004. Methods Maternal and cord serum samples were collected at delivery, and analyzed for PCBs using high-resolution gas chromatography. The Bayley Scales of Infant Development -II (BSID) were administered at 16 months of age to over 750 children who also had prenatal PCB measurements. Results Based on final multivariate-adjusted linear regression model, maternal mono-ortho-substituted PCBs were significantly associated with lower scores on both the psychomotor (PDI) and mental development indices (MDI). Also a significant association between cord mono-ortho-substituted PCBs and reduced PDI was observed, but the association with MDI was marginal (p = 0.05). Anti-estrogenic and di-ortho-substituted PCBs did not show any statistically significant association with cognitive scores, but a suggestive association between di-ortho-substituted PCBs measured in cord serum and poorer PDI was observed. Conclusion Children with higher prenatal mono-ortho-substituted PCB exposures performed more poorly on the Bayley Scales. Evidence from this and other studies suggests that prenatal dioxin-like PCB exposure, including mono-ortho congeners, may interfere with brain development in utero. Non-dioxin-like di-ortho-substituted PCBs require further investigation

Fungal Planet description sheets : 951–1041

Novel species of fungi described in this study include those from various countries as follows: Antarctica,Apenidiella antarctica from permafrost, Cladosporium fildesense from an unidentified marine sponge. Argentina,Geastrum wrightii on humus in mixed forest. Australia, Golovinomyces glandulariae on Glandularia aristigera,Neoanungitea eucalyptorum on leaves of Eucalyptus grandis, Teratosphaeria corymbiicola on leaves of Corymbiaficifolia, Xylaria eucalypti on leaves of Eucalyptus radiata. Brazil, Bovista psammophila on soil, Fusarium awaxy onrotten stalks of Zea mays, Geastrum lanuginosum on leaf litter covered soil, Hermetothecium mikaniae-micranthae(incl. Hermetothecium gen. nov.) on Mikania micrantha, Penicillium reconvexovelosoi in soil, Stagonosporopsis vannacciifrom pod of Glycine max. British Virgin Isles, Lactifluus guanensis on soil. Canada, Sorocybe oblongisporaon resin of Picea rubens. Chile, Colletotrichum roseum on leaves of Lapageria rosea. China, Setophoma cavernafrom carbonatite in Karst cave. Colombia, Lareunionomyces eucalypticola on leaves of Eucalyptus grandis. CostaRica, Psathyrella pivae on wood. Cyprus, Clavulina iris on calcareous substrate. France, Chromosera ambiguaand Clavulina iris var. occidentalis on soil. French West Indies, Helminthosphaeria hispidissima on dead wood.Guatemala, Talaromyces guatemalensis in soil. Malaysia, Neotracylla pini (incl. Tracyllales ord. nov. and Neotracyllagen. nov.) and Vermiculariopsiella pini on needles of Pinus tecunumanii. New Zealand, Neoconiothyriumviticola on stems of Vitis vinifera, Parafenestella pittospori on Pittosporum tenuifolium, Pilidium novae-zelandiaeon Phoenix sp. Pakistan, Russula quercus-floribundae on forest floor. Portugal, Trichoderma aestuarinum fromsaline water. Russia, Pluteus liliputianus on fallen branch of deciduous tree, Pluteus spurius on decaying deciduous wood or soil. South Africa, Alloconiothyrium encephalarti, Phyllosticta encephalarticola and Neothyrostromaencephalarti (incl. Neothyrostroma gen. nov.) on leaves of Encephalartos sp., Chalara eucalypticola on leaf spots ofEucalyptus grandis x urophylla, Clypeosphaeria oleae on leaves of Olea capensis, Cylindrocladiella postalofficiumon leaf litter of Sideroxylon inerme, Cylindromonium eugeniicola (incl. Cylindromonium gen. nov.) on leaf litter ofEugenia capensis, Cyphellophora goniomatis on leaves of Gonioma kamassi, Nothodactylaria nephrolepidis (incl.Nothodactylaria gen. nov. and Nothodactylariaceae fam. nov.) on leaves of Nephrolepis exaltata, Falcocladiumeucalypti and Gyrothrix eucalypti on leaves of Eucalyptus sp., Gyrothrix oleae on leaves of Olea capensis subsp.macrocarpa, Harzia metro-sideri on leaf litter of Metrosideros sp., Hippopotamyces phragmitis (incl. Hippopotamycesgen. nov.) on leaves of Phragmites australis, Lectera philenopterae on Philenoptera violacea, Leptosilliamayteni on leaves of Maytenus heterophylla, Lithohypha aloicola and Neoplatysporoides aloes on leaves of Aloesp., Millesimomyces rhoicissi (incl. Millesimomyces gen. nov.) on leaves of Rhoicissus digitata, Neodevriesiastrelitziicola on leaf litter of Strelitzia nicolai, Neokirramyces syzygii (incl. Neokirramyces gen. nov.) on leaf spots of Syzygium sp., Nothoramichloridium perseae (incl. Nothoramichloridium gen. nov. and Anungitiomycetaceae fam.nov.) on leaves of Persea americana, Paramycosphaerella watsoniae on leaf spots of Watsonia sp., Penicilliumcuddlyae from dog food, Podocarpomyces knysnanus (incl. Podocarpomyces gen. nov.) on leaves of Podocarpusfalcatus, Pseudocercospora heteropyxidicola on leaf spots of Heteropyxis natalensis, Pseudopenidiella podocarpi,Scolecobasidium podocarpi and Ceramothyrium podocarpicola on leaves of Podocarpus latifolius, Scolecobasidiumblechni on leaves of Blechnum capense, Stomiopeltis syzygii on leaves of Syzygium chordatum, Strelitziomycesknysnanus (incl. Strelitziomyces gen. nov.) on leaves of Strelitzia alba, Talaromyces clemensii from rotting wood ingoldmine, Verrucocladosporium visseri on Carpobrotus edulis. Spain, Boletopsis mediterraneensis on soil, Calycinacortegadensisi on a living twig of Castanea sativa, Emmonsiellopsis tuberculata in fluvial sediments, Mollisia cortegadensison dead attached twig of Quercus robur, Psathyrella ovispora on soil, Pseudobeltrania lauri on leaf litterof Laurus azorica, Terfezia dunensis in soil, Tuber lucentum in soil, Venturia submersa on submerged plant debris.Thailand, Cordyceps jakajanicola on cicada nymph, Cordyceps kuiburiensis on spider, Distoseptispora caricis onleaves of Carex sp., Ophiocordyceps khonkaenensis on cicada nymph. USA, Cytosporella juncicola and Davidiellomycesjuncicola on culms of Juncus effusus, Monochaetia massachusettsianum from air sample, Neohelicomycesmelaleucae and Periconia neobrittanica on leaves of Melaleuca styphelioides x lanceolata, Pseudocamarosporiumeucalypti on leaves of Eucalyptus sp., Pseudogymnoascus lindneri from sediment in a mine, Pseudogymnoascusturneri from sediment in a railroad tunnel, Pulchroboletus sclerotiorum on soil, Zygosporium pseudomasonii onleaf of Serenoa repens. Vietnam, Boletus candidissimus and Veloporphyrellus vulpinus on soil. Morphological andculture characteristics are supported by DNA barcodes

Measurement of single top-quark production in association with a W boson in the single-lepton channel at \sqrt{s} = 8\,\text {TeV} with the ATLAS detector

The production cross-section of a top quark in association with a W boson is measured using proton–proton collisions at \sqrt{s} = 8\,\text {TeV}. The dataset corresponds to an integrated luminosity of 20.2\,\text {fb}^{-1}, and was collected in 2012 by the ATLAS detector at the Large Hadron Collider at CERN. The analysis is performed in the single-lepton channel. Events are selected by requiring one isolated lepton (electron or muon) and at least three jets. A neural network is trained to separate the tW signal from the dominant t{\bar{t}} background. The cross-section is extracted from a binned profile maximum-likelihood fit to a two-dimensional discriminant built from the neural-network output and the invariant mass of the hadronically decaying W boson. The measured cross-section is \sigma _{tW} = 26 \pm 7\,\text {pb}, in good agreement with the Standard Model expectation

Measurement of the energy asymmetry in t(t)over-barj production at 13 TeV with the ATLAS experiment and interpretation in the SMEFT framework

A measurement of the energy asymmetry in jet-associated top-quark pair production is presented using $$139\,{\mathrm {fb}}^{-1}$$ 139 fb - 1 of data collected by the ATLAS detector at the Large Hadron Collider during pp collisions at $$\sqrt{s}=13\,\text {TeV}$$ s = 13 TeV . The observable measures the different probability of top and antitop quarks to have the higher energy as a function of the jet scattering angle with respect to the beam axis. The energy asymmetry is measured in the semileptonic $$t{\bar{t}}$$ t t ¯ decay channel, and the hadronically decaying top quark must have transverse momentum above $$350\,\text {GeV}$$ 350 GeV . The results are corrected for detector effects to particle level in three bins of the scattering angle of the associated jet. The measurement agrees with the SM prediction at next-to-leading-order accuracy in quantum chromodynamics in all three bins. In the bin with the largest expected asymmetry, where the jet is emitted perpendicular to the beam, the energy asymmetry is measured to be $$-0.043\pm 0.020$$ - 0.043 ± 0.020 , in agreement with the SM prediction of $$-0.037\pm 0.003$$ - 0.037 ± 0.003 . Interpreting this result in the framework of the Standard Model effective field theory (SMEFT), it is shown that the energy asymmetry is sensitive to the top-quark chirality in four-quark operators and is therefore a valuable new observable in global SMEFT fits

Measurements of electroweak Wjj production and constraints on anomalous gauge couplings with the ATLAS detector

Measurements of the electroweak production of a W boson in association with two jets at high dijet invariant mass are performed using root s = 7 and 8 TeV proton-proton collision data produced by the Large Hadron Collider, corresponding respectively to 4.7 and 20.2 fb(-1) of integrated luminosity collected by the ATLAS detector. The measurements are sensitive to the production of a W boson via a triple-gauge-boson vertex and include both the fiducial and differential cross sections of the electroweak process

Measurement of jet fragmentation in Pb+Pb and pp collisions at √SNN = 2.76 TeV with the ATLAS detector at the LHC

The distributions of transverse momentum and longitudinal momentum fraction of charged particles in jets are measured in Pb+Pb and pp collisions with the ATLAS detector at the LHC. The distributions are measured as a function of jet transverse momentum and rapidity. The analysis utilises an integrated luminosity of 0.14 nb−1−1 of Pb+Pb data and 4.0 pb−1−1 of pp data collected in 2011 and 2013, respectively, at the same centre-of-mass energy of 2.76 TeV per colliding nucleon pair. The distributions measured in pp collisions are used as a reference for those measured in Pb+Pb collisions in order to evaluate the impact on the internal structure of jets from the jet energy loss of fast partons propagating through the hot, dense medium created in heavy-ion collisions. Modest but significant centrality-dependent modifications of fragmentation functions in Pb+Pb collisions with respect to those in pp collisions are seen. No significant dependence of modifications on jet pTpT and rapidity selections is observed except for the fragments with the highest transverse momenta for which some reduction of yields is observed for more forward jets

Study of the rare decays of B-s(0) and B-0 into muon pairs from data collected during the LHC Run 1 with the ATLAS detector

A study of the decays B0s→μ+μ−Bs0→μ+μ− and B0→μ+μ−B0→μ+μ− has been performed using data corresponding to an integrated luminosity of 25 fb −1−1 of 7 and 8 TeV proton–proton collisions collected with the ATLAS detector during the LHC Run 1. For the B0B0 dimuon decay, an upper limit on the branching fraction is set at B(B0→μ+μ−)<4.2×10−10B(B0→μ+μ−)<4.2×10−10 at 95 % confidence level. For B0sBs0 , the branching fraction B(B0s→μ+μ−)=(0.9+1.1−0.8)×10−9B(Bs0→μ+μ−)=(0.9−0.8+1.1)×10−9 is measured. The results are consistent with the Standard Model expectation with a p value of 4.8 %, corresponding to 2.0 standard deviations

Search for new phenomena in high-mass final states with a photon and a jet from pp collisions at root s=13 TeV with the ATLAS detector

A search is performed for new phenomena in events having a photon with high transverse momentum and a jet collected in 36.7 fb−1 of proton–proton collisions at a centre-of-mass energy of s√ = 13 TeV recorded with the ATLAS detector at the Large Hadron Collider. The invariant mass distribution of the leading photon and jet is examined to look for the resonant production of new particles or the presence of new high-mass states beyond the Standard Model. No significant deviation from the background-only hypothesis is observed and cross-section limits for generic Gaussian-shaped resonances are extracted. Excited quarks hypothesized in quark compositeness models and high-mass states predicted in quantum black hole models with extra dimensions are also examined in the analysis. The observed data exclude, at 95% confidence level, the mass range below 5.3 TeV for excited quarks and 7.1 TeV (4.4 TeV) for quantum black holes in the Arkani-Hamed–Dimopoulos–Dvali (Randall–Sundrum) model with six (one) extra dimensions

Measurement of the W-boson mass in pp collisions at root s=7 TeV with the ATLAS detector

A measurement of the mass of the W boson is presented based on proton–proton collision data recorded in 2011 at a centre-of-mass energy of 7 TeV with the ATLAS detector at the LHC, and corresponding to 4.6 fb−1 of integrated luminosity. The selected data sample consists of 7.8 × 106 candidates in the W → μν channel and 5.9 × 106 candidates in the W → eν channel. The W-boson mass is obtained from template fits to the reconstructed distributions of the charged lepton transverse momentum and of the W boson transverse mass in the electron and muon decay channels, yielding mW = 80370 ± 7 (stat.) ± 11(exp. syst.) ± 14 (mod. syst.) MeV = 80370 ± 19 MeV, where the first uncertainty is statistical, the second corresponds to the experimental systematic uncertainty, and the third to the physics-modelling systematic uncertainty. A measurement of the mass difference between the W+ and W− bosons yields mW+ − mW− = − 29 ± 28 MeV