Soil biochemistry and microbial activity in vineyards under conventional and organic management at Northeast Brazil.

The São Francisco Submedium Valley is located at the Brazilian semiarid region and is an important center for irrigated fruit growing. This region is responsible for 97% of the national exportation of table grapes, including seedless grapes. Based on the fact that orgThe São Francisco Submedium Valley is located at the Brazilian semiarid region and is an important center for irrigated fruit growing. This region is responsible for 97% of the national exportation of table grapes, including seedless grapes. Based on the fact that organic fertilization can improve soil quality, we compared the effects of conventional and organic soil management on microbial activity and mycorrhization of seedless grape crops. We measured glomerospores number, most probable number (MPN) of propagules, richness of arbuscular mycorrhizal fungi (AMF) species, AMF root colonization, EE-BRSP production, carbon microbial biomass (C-MB), microbial respiration, fluorescein diacetate hydrolytic activity (FDA) and metabolic coefficient (qCO2). The organic management led to an increase in all variables with the exception of EE-BRSP and qCO2. Mycorrhizal colonization increased from 4.7% in conventional crops to 15.9% in organic crops. Spore number ranged from 4.1 to 12.4 per 50 g-1 soil in both management systems. The most probable number of AMF propagules increased from 79 cm-3 soil in the conventional system to 110 cm-3 soil in the organic system. Microbial carbon, CO2 emission, and FDA activity were increased by 100 to 200% in the organic crop. Thirteen species of AMF were identified, the majority in the organic cultivation system. Acaulospora excavata, Entrophospora infrequens, Glomus sp.3 and Scutellospora sp. were found only in the organically managed crop. S. gregaria was found only in the conventional crop. Organically managed vineyards increased mycorrhization and general soil microbial activity

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

DES15E2mlf: a spectroscopically confirmed superluminous supernova that exploded 3.5 Gyr after the big bang

We present the Dark Energy Survey (DES) discovery of DES15E2mlf, the most distant superluminous supernova (SLSN) spectroscopically confirmed to date. The light curves and Gemini spectroscopy of DES15E2mlf indicate that it is a Type I superluminous supernova (SLSN-I) at z = 1.861 (a lookback time of ∼10 Gyr) and peaking at MAB = −22.3 ± 0.1 mag. Given the high redshift, our data probe the rest-frame ultraviolet (1400–3500 Å) properties of the SN, finding velocity of the C III feature changes by ∼5600 km s−1 over 14 d around maximum light. We find the host galaxy of DES15E2mlf has a stellar mass of 3.5+3.6 −2.4 × 109 M, which is more massive than the typical SLSN-I host galaxy

Measurement of the splashback feature around SZ-selected Galaxy clusters with DES, SPT, and ACT

We present a detection of the splashback feature around galaxy clusters selected using the Sunyaev–Zel’dovich (SZ) signal. Recent measurements of the splashback feature around optically selected galaxy clusters have found that the splashback radius, rsp, is smaller than predicted by N-body simulations. A possible explanation for this discrepancy is that rsp inferred from the observed radial distribution of galaxies is affected by selection effects related to the optical cluster-finding algorithms. We test this possibility by measuring the splashback feature in clusters selected via the SZ effect in data from the South Pole Telescope SZ survey and the Atacama Cosmology Telescope Polarimeter survey. The measurement is accomplished by correlating these cluster samples with galaxies detected in the Dark Energy Survey Year 3 data. The SZ observable used to select clusters in this analysis is expected to have a tighter correlation with halo mass and to be more immune to projection effects and aperture-induced biases, potentially ameliorating causes of systematic error for optically selected clusters. We find that the measured rsp for SZ-selected clusters is consistent with the expectations from simulations, although the small number of SZ-selected clusters makes a precise comparison difficult. In agreement with previous work, when using optically selected redMaPPer clusters with similar mass and redshift distributions, rsp is ∼2σ smaller than in the simulations. These results motivate detailed investigations of selection biases in optically selected cluster catalogues and exploration of the splashback feature around larger samples of SZ-selected clusters. Additionally, we investigate trends in the galaxy profile and splashback feature as a function of galaxy colour, finding that blue galaxies have profiles close to a power law with no discernible splashback feature, which is consistent with them being on their first infall into the cluster

First cosmology results using SNe Ia from the dark energy survey: analysis, systematic uncertainties, and validation

International audienceWe present the analysis underpinning the measurement of cosmological parameters from 207 spectroscopically classified type Ia supernovae (SNe Ia) from the first three years of the Dark Energy Survey Supernova Program (DES-SN), spanning a redshift range of 0.01