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The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) Stellar Library (MaStar) is a large collection of high-quality empirical stellar spectra designed to cover all spectral types and ideal for use in the stellar population analysis of galaxies observed in the MaNGA survey. The library contains 59,266 spectra of 24,130 unique stars with spectral resolutionR∼ 1800 and covering a wavelength range of 3622–10,354 Å. In this work, we derive five physical parameters for each spectrum in the library: effective temperature (T_eff), surface gravity ($\log g$), metallicity ([Fe/H]), microturbulent velocity ($\log (v_{\mathrm{micro}})$), and alpha-element abundance ([α/Fe]). These parameters are derived with a flexible data-driven algorithm that uses a neural network model. We train a neural network using the subset of 1675 MaStar targets that have also been observed in the Apache Point Observatory Galactic Evolution Experiment (APOGEE), adopting the independently-derived APOGEE Stellar Parameter and Chemical Abundance Pipeline parameters for this reference set. For the regions of parameter space not well represented by the APOGEE training set (7000 ≤T≤ 30,000 K), we supplement with theoretical model spectra. We present our derived parameters along with an analysis of the uncertainties and comparisons to other analyses from the literature.

 

The Sloan Digital Sky Survey IV Mapping Nearby Galaxies at APO (MaNGA) program has been operating from 2014 to 2020, and has now observed a sample of 9269 galaxies in the low redshift universe (z ∼ 0.05) with integral-field spectroscopy. With rest-optical (λλ0.36-1.0 μm) spectral resolution R ∼ 2000 the instrumental spectral line-spread function (LSF) typically has 1σ width of about 70 km s-1, which poses a challenge for the study of the typically 20-30 km s-1 velocity dispersion of the ionized gas in present-day disk galaxies. In this contribution, we present a major revision of the MaNGA data pipeline architecture, focusing particularly on a variety of factors impacting the effective LSF (e.g., under-sampling, spectral rectification, and data cube construction). Through comparison with external assessments of the MaNGA data provided by substantially higher-resolution R ∼ 10,000 instruments, we demonstrate that the revised MPL-10 pipeline measures the instrumental LSF sufficiently accurately (≤0.6% systematic, 2% random around the wavelength of Hα) that it enables reliable measurements of astrophysical velocity dispersions σHα ∼ 20 km s-1 for spaxels with emission lines detected at signal-to-noise ratio > 50. Velocity dispersions derived from [O II], Hβ, [O III], [N II], and [S II] are consistent with those derived from Hα to within about 2% at σHα > 30 km s-1. Although the impact of these changes to the estimated LSF will be minimal at velocity dispersions greater than about 100 km s-1, scientific results from previous data releases that are based on dispersions far below the instrumental resolution should be reevaluated. 

Abstract Varroa destructor is an ectoparasitic mite of immature and adult honey bees that can transmit several single-stranded RNA viruses to its host. Varroa reproduce in brood cells, and mite populations increase as colonies produce brood in spring and summer. Mite numbers also can sharply rise, particularly in the fall, by the migration of varroa into hives on foragers. Colonies with high levels of varroa and viruses often die over the winter. Feeding colonies pollen might keep virus levels low and improve survival because of the positive effects of pollen on immunity and colony growth. We compared varroa and virus levels and overwinter survival in colonies with (fed) and without (unfed) supplemental pollen. We also measured the frequency of capturing foragers with mites (FWM) at colony entrances to determine its relationship to varroa and virus levels. Colonies fed supplemental pollen were larger than unfed colonies and survived longer. Varroa populations and levels of Deformed wing virus (DWV) rose throughout the season, and were similar between fed and unfed colonies. The growth of varroa populations was correlated with FWM in fed and unfed colonies, and significantly affected DWV levels. Increasing frequencies of FWM and the effects on varroa populations might reduce the positive influence of supplemental pollen on immune function. However, pollen feeding can stimulate colony growth and this can improve colony survival.