Longitudinal patterns in an Arkansas River Valley stream: an Application of the River Continuum Concept

The River Continuum Concept (RCC) provides the framework for studying how lotic ecosystems vary from headwater streams to large rivers. The RCC was developed in streams in eastern deciduous forests of North America, but watershed characteristics and land uses differ across ecoregions, presenting unique opportunities to study how predictions of the RCC may differ across regions. Additionally, RCC predictions may vary due to the influence of fishes, but few studies have used fish taxa as a metric for evaluating predictions of the RCC. Our goal was to determine if RCC predictions for stream orders 1 through 5 were supported by primary producer, macroinvertebrate, and fish communities in Cadron Creek of the Arkansas River Valley. We sampled chlorophyll a, macroinvertebrates, and fishes at five stream reaches across a gradient of watershed size. Contrary to RCC predictions, chlorophyll a did not increase in concentration with catchment size. As the RCC predicts, fish and macroinvertebrate diversity increased with catchment size. Shredding and collecting macroinvertebrate taxa supported RCC predictions, respectively decreasing and increasing in composition as catchment area increased. Herbivorous and predaceous fish did not follow RCC predictions; however, surface-water column feeding fish were abundant at all sites as predicted. We hypothesize some predictions of the RCC were not supported in headwater reaches of this system due to regional differences in watershed characteristics and altered resource availability due to land use surrounding sampling sites

The triggering probability of radio-loud AGN: A comparison of high and low excitation radio galaxies in hosts of different colors

Low luminosity radio-loud active galactic nuclei (AGN) are generally found in massive red elliptical galaxies, where they are thought to be powered through gas accretion from their surrounding hot halos in a radiatively inefficient manner. These AGN are often referred to as "low-excitation" radio galaxies (LERGs). When radio-loud AGN are found in galaxies with a young stellar population and active star formation, they are usually high-power radiatively-efficient radio AGN ("high-excitation", HERG). Using a sample of low-redshift radio galaxies identified within the Sloan Digital Sky Survey (SDSS), we determine the fraction of galaxies that host a radio-loud AGN, $f_{RL}$, as a function of host galaxy stellar mass, $M_*$, star formation rate, color (defined by the 4000 \angstrom break strength), radio luminosity and excitation state (HERG/LERG). We find the following: 1. LERGs are predominantly found in red galaxies. 2. The radio-loud AGN fraction of LERGs hosted by galaxies of any color follows a $f^{LE}_{RL} \propto M^{2.5}_*$ power law. 3. The fraction of red galaxies hosting a LERG decreases strongly for increasing radio luminosity. For massive blue galaxies this is not the case. 4. The fraction of green galaxies hosting a LERG is lower than that of either red or blue galaxies, at all radio luminosities. 5. The radio-loud AGN fraction of HERGs hosted by galaxies of any color follows a $f^{HE}_{RL} \propto M^{1.5}_*$ power law. 6. HERGs have a strong preference to be hosted by green or blue galaxies. 7. The fraction of galaxies hosting a HERG shows only a weak dependence on radio luminosity cut. 8. For both HERGs and LERGs, the hosting probability of blue galaxies shows a strong dependence on star formation rate. This is not observed in galaxies of a different color.[abridged]Comment: 7 pages, 6 figure

New Approaches To Photometric Redshift Prediction Via Gaussian Process Regression In The Sloan Digital Sky Survey

Expanding upon the work of Way and Srivastava 2006 we demonstrate how the use of training sets of comparable size continue to make Gaussian process regression (GPR) a competitive approach to that of neural networks and other least-squares fitting methods. This is possible via new large size matrix inversion techniques developed for Gaussian processes (GPs) that do not require that the kernel matrix be sparse. This development, combined with a neural-network kernel function appears to give superior results for this problem. Our best fit results for the Sloan Digital Sky Survey (SDSS) Main Galaxy Sample using u,g,r,i,z filters gives an rms error of 0.0201 while our results for the same filters in the luminous red galaxy sample yield 0.0220. We also demonstrate that there appears to be a minimum number of training-set galaxies needed to obtain the optimal fit when using our GPR rank-reduction methods. We find that morphological information included with many photometric surveys appears, for the most part, to make the photometric redshift evaluation slightly worse rather than better. This would indicate that most morphological information simply adds noise from the GP point of view in the data used herein. In addition, we show that cross-match catalog results involving combinations of the Two Micron All Sky Survey, SDSS, and Galaxy Evolution Explorer have to be evaluated in the context of the resulting cross-match magnitude and redshift distribution. Otherwise one may be misled into overly optimistic conclusions.Comment: 32 pages, ApJ in Press, 2 new figures, 1 new table of comparison methods, updated discussion, references and typos to reflect version in Pres

Two novel approaches for photometric redshift estimation based on SDSS and 2MASS databases

We investigate two training-set methods: support vector machines (SVMs) and Kernel Regression (KR) for photometric redshift estimation with the data from the Sloan Digital Sky Survey Data Release 5 and Two Micron All Sky Survey databases. We probe the performances of SVMs and KR for different input patterns. Our experiments show that the more parameters considered, the accuracy doesn't always increase, and only when appropriate parameters chosen, the accuracy can improve. Moreover for different approaches, the best input pattern is different. With different parameters as input, the optimal bandwidth is dissimilar for KR. The rms errors of photometric redshifts based on SVM and KR methods are less than 0.03 and 0.02, respectively. Finally the strengths and weaknesses of the two approaches are summarized. Compared to other methods of estimating photometric redshifts, they show their superiorities, especially KR, in terms of accuracy.Comment: accepted for publication in ChJA

Properties of Disks and Bulges of Spiral and Lenticular Galaxies in the Sloan Digital Sky Survey

A bulge-disk decomposition is made for 737 spiral and lenticular galaxies drawn from a SDSS galaxy sample for which morphological types are estimated. We carry out the bulge-disk decomposition using the growth curve fitting method. It is found that bulge properties, effective radius, effective surface brightness, and also absolute magnitude, change systematically with the morphological sequence; from early to late types, the size becomes somewhat larger, and surface brightness and luminosity fainter. In contrast disks are nearly universal, their properties remaining similar among disk galaxies irrespective of detailed morphologies from S0 to Sc. While these tendencies were often discussed in previous studies, the present study confirms them based on a large homogeneous magnitude-limited field galaxy sample with morphological types estimated. The systematic change of bulge-to-total luminosity ratio, $B/T$, along the morphological sequence is therefore not caused by disks but mostly by bulges. It is also shown that elliptical galaxies and bulges of spiral galaxies are unlikely to be in a single sequence. We infer the stellar mass density (in units of the critical mass density) to be $\Omega=$0.0021 for spheroids, i.e., elliptical galaxies plus bulges of spiral galaxies, and $\Omega=$0.00081 for disks.Comment: 30 pages, 9 figure

Reducing Zero-point Systematics in Dark Energy Supernova Experiments

We study the effect of filter zero-point uncertainties on future supernova dark energy missions. Fitting for calibration parameters using simultaneous analysis of all Type Ia supernova standard candles achieves a significant improvement over more traditional fit methods. This conclusion is robust under diverse experimental configurations (number of observed supernovae, maximum survey redshift, inclusion of additional systematics). This approach to supernova fitting considerably eases otherwise stringent mission calibration requirements. As an example we simulate a space-based mission based on the proposed JDEM satellite; however the method and conclusions are general and valid for any future supernova dark energy mission, ground or space-based.Comment: 30 pages,8 figures, 5 table, one reference added, submitted to Astroparticle Physic

Spectroscopic Target Selection in the Sloan Digital Sky Survey: The Quasar Sample

We describe the algorithm for selecting quasar candidates for optical spectroscopy in the Sloan Digital Sky Survey. Quasar candidates are selected via their non-stellar colors in "ugriz" broad-band photometry, and by matching unresolved sources to the FIRST radio catalogs. The automated algorithm is sensitive to quasars at all redshifts lower than z=5.8. Extended sources are also targeted as low-redshift quasar candidates in order to investigate the evolution of Active Galactic Nuclei (AGN) at the faint end of the luminosity function. Nearly 95% of previously known quasars are recovered (based on 1540 quasars in 446 square degrees). The overall completeness, estimated from simulated quasars, is expected to be over 90%, whereas the overall efficiency (quasars:quasar candidates) is better than 65%. The selection algorithm targets ultraviolet excess quasars to i^*=19.1 and higher-redshift (z>3) quasars to i^*=20.2, yielding approximately 18 candidates per square degree. In addition to selecting ``normal'' quasars, the design of the algorithm makes it sensitive to atypical AGN such as Broad Absorption Line quasars and heavily reddened quasars.Comment: 62 pages, 15 figures (8 color), 8 tables. Accepted by AJ. For a version with higher quality color figures, see http://archive.stsci.edu/sdss/quasartarget/RichardsGT_qsotarget.preprint.p

Faint NUV/FUV Standards from Swift/UVOT, GALEX and SDSS Photometry

At present, the precision of deep ultraviolet photometry is somewhat limited by the dearth of faint ultraviolet standard stars. In an effort to improve this situation, we present a uniform catalog of eleven new faint (u sim17) ultraviolet standard stars. High-precision photometry of these stars has been taken from the Sloan Digital Sky Survey and Galaxy Evolution Explorer and combined with new data from the Swift Ultraviolet Optical Telescope to provide precise photometric measures extending from the Near Infrared to the Far Ultraviolet. These stars were chosen because they are known to be hot (20,000 < T_eff < 50,000 K) DA white dwarfs with published Sloan spectra that should be photometrically stable. This careful selection allows us to compare the combined photometry and Sloan spectroscopy to models of pure hydrogen atmospheres to both constrain the underlying properties of the white dwarfs and test the ability of white dwarf models to predict the photometric measures. We find that the photometry provides good constraint on white dwarf temperatures, which demonstrates the ability of Swift/UVOT to investigate the properties of hot luminous stars. We further find that the models reproduce the photometric measures in all eleven passbands to within their systematic uncertainties. Within the limits of our photometry, we find the standard stars to be photometrically stable. This success indicates that the models can be used to calibrate additional filters to our standard system, permitting easier comparison of photometry from heterogeneous sources. The largest source of uncertainty in the model fitting is the uncertainty in the foreground reddening curve, a problem that is especially acute in the UV.Comment: Accepted for publication in Astrophysical Journal. 31 pages, 13 figures, electronic tables available from ApJ or on reques

Discovery of Four Gravitationally Lensed Quasars from the Sloan Digital Sky Survey

We present the discovery of four gravitationally lensed quasars selected from the spectroscopic quasar catalog of the Sloan Digital Sky Survey. We describe imaging and spectroscopic follow-up observations that support the lensing interpretation of the following four quasars: SDSS J0832+0404 (image separation \theta=1.98", source redshift z_s=1.115, lens redshift z_l=0.659); SDSS J1216+3529 (\theta=1.49", z_s=2.012); SDSS J1322+1052 (\theta=2.00", z_s=1.716); and SDSS J1524+4409 (\theta=1.67", z_s=1.210, z_l=0.320). Each system has two lensed images. We find that the fainter image component of SDSS J0832+0404 is significantly redder than the brighter component, perhaps because of differential reddening by the lensing galaxy. The lens potential of SDSS J1216+3529 might be complicated by the presence of a secondary galaxy near the main lensing galaxy.Comment: 25 pages, 10 figures, 6 tables, accepted for publication in A

A Precision Photometric Comparison between SDSS-II and CSP Type Ia Supernova Data

Consistency between Carnegie Supernova Project (CSP) and SDSS-II supernova (SN) survey ugri measurements has been evaluated by comparing SDSS and CSP photometry for nine spectroscopically confirmed Type Ia supernova observed contemporaneously by both programs. The CSP data were transformed into the SDSS photometric system. Sources of systematic uncertainty have been identified, quantified, and shown to be at or below the 0.023 magnitude level in all bands. When all photometry for a given band is combined, we find average magnitude differences of equal to or less than 0.011 magnitudes in ugri, with rms scatter ranging from 0.043 to 0.077 magnitudes. The u band agreement is promising, with the caveat that only four of the nine supernovae are well-observed in u and these four exhibit an 0.038 magnitude supernova-to-supernova scatter in this filter.Comment: This paper has been accepted for publication in The Astronomical Journa