TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

SN 2018gjx reveals that some SNe Ibn are SNe IIb exploding in dense circumstellar material

We present the data and analysis of SN 2018gjx, an unusual low-luminosity transient with three distinct spectroscopic phases. Phase I shows a hot blue spectrum with signatures of ionized circumstellar material (CSM), Phase II has the appearance of broad SN features, consistent with those seen in a Type IIb supernova at maximum light, and Phase III is that of a supernova interacting with helium-rich CSM, similar to a Type Ibn supernova. This event provides an apparently rare opportunity to view the inner workings of an interacting supernova. The observed properties can be explained by the explosion of a star in an aspherical CSM. The initial light is emitted from an extended CSM (∼4000 R⊙), which ionizes the exterior unshocked material. Some days after, the SN photosphere envelops this region, leading to the appearance of a SN IIb. Over time, the photosphere recedes in velocity space, revealing interaction between the supernova ejecta and the CSM that partially obscures the supernova nebular phase. Modelling of the initial spectrum reveals a surface composition consistent with compact H-deficient Wolf–Rayet and Luminous Blue Variable (LBV) stars. Such configurations may not be unusual, with SNe IIb being known to have signs of interaction so at least some SNe IIb and SNe Ibn may be the same phenomena viewed from different angles, or possibly with differing CSM configurations

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

Worldwide trends in population-based survival for children, adolescents, and young adults diagnosed with leukaemia, by subtype, during 2000–14 (CONCORD-3) : analysis of individual data from 258 cancer registries in 61 countries

Background Leukaemias comprise a heterogenous group of haematological malignancies. In CONCORD-3, we analysed data for children (aged 0–14 years) and adults (aged 15–99 years) diagnosed with a haematological malignancy during 2000–14 in 61 countries. Here, we aimed to examine worldwide trends in survival from leukaemia, by age and morphology, in young patients (aged 0–24 years). Methods We analysed data from 258 population-based cancer registries in 61 countries participating in CONCORD-3 that submitted data on patients diagnosed with leukaemia. We grouped patients by age as children (0–14 years), adolescents (15–19 years), and young adults (20–24 years). We categorised leukaemia subtypes according to the International Classification of Childhood Cancer (ICCC-3), updated with International Classification of Diseases for Oncology, third edition (ICD-O-3) codes. We estimated 5-year net survival by age and morphology, with 95% CIs, using the non-parametric Pohar-Perme estimator. To control for background mortality, we used life tables by country or region, single year of age, single calendar year and sex, and, where possible, by race or ethnicity. All-age survival estimates were standardised to the marginal distribution of young people with leukaemia included in the analysis. Findings 164563 young people were included in this analysis: 121328 (73·7%) children, 22963 (14·0%) adolescents, and 20272 (12·3%) young adults. In 2010–14, the most common subtypes were lymphoid leukaemia (28205 [68·2%] patients) and acute myeloid leukaemia (7863 [19·0%] patients). Age-standardised 5-year net survival in children, adolescents, and young adults for all leukaemias combined during 2010–14 varied widely, ranging from 46% in Mexico to more than 85% in Canada, Cyprus, Belgium, Denmark, Finland, and Australia. Individuals with lymphoid leukaemia had better age-standardised survival (from 43% in Ecuador to ≥80% in parts of Europe, North America, Oceania, and Asia) than those with acute myeloid leukaemia (from 32% in Peru to ≥70% in most high-income countries in Europe, North America, and Oceania). Throughout 2000–14, survival from all leukaemias combined remained consistently higher for children than adolescents and young adults, and minimal improvement was seen for adolescents and young adults in most countries. Interpretation This study offers the first worldwide picture of population-based survival from leukaemia in children, adolescents, and young adults. Adolescents and young adults diagnosed with leukaemia continue to have lower survival than children. Trends in survival from leukaemia for adolescents and young adults are important indicators of the quality of cancer management in this age group.peer-reviewe

Global survival trends for brain tumors, by histology: analysis of individual records for 556,237 adults diagnosed in 59 countries during 2000–2014 (CONCORD-3)

Background: Survival is a key metric of the effectiveness of a health system in managing cancer. We set out to provide a comprehensive examination of worldwide variation and trends in survival from brain tumors in adults, by histology. Methods: We analyzed individual data for adults (15–99 years) diagnosed with a brain tumor (ICD-O-3 topography code C71) during 2000–2014, regardless of tumor behavior. Data underwent a 3-phase quality control as part of CONCORD-3. We estimated net survival for 11 histology groups, using the unbiased nonparametric Pohar Perme estimator. Results: The study included 556,237 adults. In 2010–2014, the global range in age-standardized 5-year net survival for the most common sub-types was broad: in the range 20%–38% for diffuse and anaplastic astrocytoma, from 4% to 17% for glioblastoma, and between 32% and 69% for oligodendroglioma. For patients with glioblastoma, the largest gains in survival occurred between 2000–2004 and 2005–2009. These improvements were more noticeable among adults diagnosed aged 40–70 years than among younger adults. Conclusions: To the best of our knowledge, this study provides the largest account to date of global trends in population-based survival for brain tumors by histology in adults. We have highlighted remarkable gains in 5-year survival from glioblastoma since 2005, providing large-scale empirical evidence on the uptake of chemoradiation at population level. Worldwide, survival improvements have been extensive, but some countries still lag behind. Our findings may help clinicians involved in national and international tumor pathway boards to promote initiatives aimed at more extensive implementation of clinical guidelines

Measurement of differential cross sections of isolated-photon plus heavy-flavour jet production in pp collisions at √s=8 TeV using the ATLAS detector

This Letter presents the measurement of differential cross sections of isolated prompt photons produced in association with a b-jet or a c-jet. These final states provide sensitivity to the heavy-flavour content of the proton and aspects related to the modelling of heavy-flavour quarks in perturbative QCD. The measurement uses proton–proton collision data at a centre-of-mass energy of 8 TeV recorded by the ATLAS detector at the LHC in 2012 corresponding to an integrated luminosity of up to 20.2 fb−1. The differential cross sections are measured for each jet flavour with respect to the transverse energy of the leading photon in two photon pseudorapidity regions: |ηγ | < 1.37 and 1.56 < |ηγ | < 2.37. The measurement covers photon transverse energies 25 < Eγ T < 400 GeV and 25 < Eγ T < 350 GeV respectively for the two |ηγ | regions. For each jet flavour, the ratio of the cross sections in the two |ηγ | regions is also measured. The measurement is corrected for detector effects and compared to leading-order and nextto-leading-order perturbative QCD calculations, based on various treatments and assumptions about the heavy-flavour content of the proton. Overall, the predictions agree well with the measurement, but some deviations are observed at high photon transverse energies. The total uncertainty in the measurement ranges between 13% and 66%, while the central γ + b measurement exhibits the smallest uncertainty, ranging from 13% to 27%, which is comparable to the precision of the theoretical predictions