The American Astronomical Society, find out more The Institute of Physics, find out more Where Do Quasar Hosts Lie with Respect to the Size–Mass Relation of Galaxies?

The evolution of the galaxy size–mass relation has been a puzzle for over a decade. High-redshift galaxies are significantly more compact than galaxies observed today at an equivalent mass, but how much of this apparent growth is driven by progenitor bias, minor mergers, secular processes, or feedback from active galactic nuclei (AGNs) is unclear. To help disentangle the physical mechanisms at work by addressing the latter, we study the size–Mstellar relation of 32 carefully selected broad-line AGN hosts at 1.2 \u3c z \u3c 1.7 (7.5 \u3c log MBH \u3c 8.5; Lbol/LEdd ≳ 0.1). Using the Hubble Space Telescope with multiband photometry and state-of-the-art modeling techniques, we measure half-light radii while accounting for uncertainties from subtracting bright central point sources. We find AGN hosts to have sizes ranging from ∼1 to 6 kpc at Mstellar ∼ (0.3–1) × 1011 M⊙. Thus, many hosts have intermediate sizes as compared to equal-mass star-forming and quiescent galaxies. While inconsistent with the idea that AGN feedback may induce an increase in galaxy sizes, this finding is consistent with hypotheses in which AGNs preferentially occur in systems with prior concentrated gas reservoirs, or are involved in a secular compaction processes perhaps responsible for building their bulges. If driven by minor mergers that do not grow central black holes as fast as they do bulge-like stellar structures, such a process would explain both the galaxy size–mass relation observed here and the evolution in the black hole–bulge mass relation described in a companion paper

The Mass Relations between Supermassive Black Holes and Their Host Galaxies at 1 \u3c z \u3c 2 with \u3cem\u3eHST\u3c/em\u3e-WFC3

Correlations between the mass of a supermassive black hole (SMBH) and the properties of its host galaxy (e.g., total stellar mass M*, luminosity Lhost) suggest an evolutionary connection. A powerful test of a coevolution scenario is to measure the relations –Lhost and –M* at high redshift and compare with local estimates. For this purpose, we acquired Hubble Space Telescope (HST) imaging with WFC3 of 32 X-ray-selected broad-line (type 1) active galactic nuclei at 1.2 \u3c z \u3c 1.7 in deep survey fields. By applying state-of-the-art tools to decompose the HST images including available ACS data, we measured the host galaxy luminosity and stellar mass along with other properties through the two-dimensional model fitting. The black hole mass () was determined using the broad Hα line, detected in the near-infrared with the Subaru Fiber Multi-Object Spectrograph, which potentially minimizes systematic effects using other indicators. We find that the observed ratio of to total M* is 2.7× larger at z ∼ 1.5 than in the local universe, while the scatter is equivalent between the two epochs. A nonevolving mass ratio is consistent with the data at the 2σ–3σ confidence level when accounting for selection effects (estimated using two independent and complementary methods) and their uncertainties. The relationship between and host galaxy total luminosity paints a similar picture. Therefore, our results cannot distinguish whether SMBHs and their total host stellar mass and luminosity proceed in lockstep or whether the growth of the former somewhat overshoots the latter, given the uncertainties. Based on a statistical estimate of the bulge-to-total mass fraction, the ratio /M*,bulge is offset from the local value by a factor of ∼7, which is significant even accounting for selection effects. Taken together, these observations are consistent with a scenario in which stellar mass is subsequently transferred from an angular momentum–supported component of the galaxy to a pressure-supported one through secular processes or minor mergers at a faster rate than mass accretion onto the SMBH

Open Science principles for accelerating trait-based science across the Tree of Life.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges

The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500

Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has quantified anthropogenic emissions for the shared socio-economic pathway (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentrations for these SSP scenarios – using the reduced-complexity climate–carbon-cycle model MAGICC7.0. We extend historical, observationally based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios, respectively. We also provide the concentration extensions beyond 2100 based on assumptions regarding the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO2 emissions. By 2150, CO2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel-driven scenario projects CO2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from 66 % for the present day to roughly 68 % to 85 % by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterizations that reflect the Oslo Line-By-Line model results. In comparison to the representative concentration pathways (RCPs), the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are more evenly spaced and extend to lower 2100 radiative forcing and temperatures. Performing two pairs of six-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the March–April–May (MAM) season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (∼5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies' projections over the next 100 to 500 years unequivocally depict a “hockey-stick” upwards shape. The SSP concentration time series derived in this study provide a harmonized set of input assumptions for long-term climate science analysis; they also provide an indication of the wide set of futures that societal developments and policy implementations can lead to – ranging from multiple degrees of future warming on the one side to approximately 1.5 ∘C warming on the other

Methodology

© The Author(s) 2019. A detailed overview of the methodologies used to develop the 2.0 °C and 1.5 °C scenario presented in this book. Starting with the overall modelling approach, the interaction of seven different models is explained which are used to calculate and developed detailed scenarios for greenhouse gas emission and energy pathways to stay within a 2.0 °C and 1.5 °C global warming limit. The following models are presented: For the non-energy GHG emission pathways, the Generalized Equal Quantile Walk (GQW)method, the land-based sequestration design method and the Carbon cycle and climate (MAGICC) model. For the energy pathways, a renewable energy resources assessment for space constrained environments ([R]E-SPACE, the transport scenario model (TRAEM), the Energy System Model (EM) and the power system model [R]E 24/7. The methodologies of an employment analysis model, and a metal resource assessment tool are outlined. These models have been used to examine the analysis of the energy scenario results

Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance.

The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche complementarity in oleaginous microbial populations from a biological wastewater treatment plant. We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekly intervals. Based on 1,364 de novo metagenome-assembled genomes, we uncover four distinct fundamental niche types. Throughout the time-series, we observe a major, transient shift in community structure, coinciding with substrate availability changes. Functional omics data reveals extensive variation in gene expression and substrate usage amongst community members. Ex situ bioreactor experiments confirm that responses occur within five hours of a pulse disturbance, demonstrating rapid adaptation by specific populations. Our results show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity, and set the foundation for future ecological engineering efforts