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We describe the model for mapping from sky brightness to the digital output of the Dark Energy Camera (DECam) and the algorithms adopted by the Dark Energy Survey (DES) for inverting this model to obtain photometric measures of celestial objects from the raw camera output. This calibration aims for fluxes that are uniform across the camera field of view and across the full angular and temporal span of the DES observations, approaching the accuracy limits set by shot noise for the full dynamic range of DES observations. The DES pipeline incorporates several substantive advances over standard detrending techniques, including principal-components-based sky and fringe subtraction; correction of the \"brighter-fatter\" nonlinearity; use of internal consistency in on-sky observations to disentangle the influences of quantum efficiency, pixel-size variations, and scattered light in the dome flats; and pixel-by-pixel characterization of instrument spectral response, through combination of internal-consistency constraints with auxiliary calibration data. This article provides conceptual derivations of the detrending/calibration steps, and the procedures for obtaining the necessary calibration data. Other publications will describe the implementation of these concepts for the DES operational pipeline, the detailed methods, and the validation that the techniques can bring DECam photometry and astrometry within 2 mmag and 3 mas, respectively, of fundamental atmospheric and statistical limits. The DES techniques should be broadly applicable to wide-field imagers.

A plant-based thermal optimum approach to irrigation scheduling provides potential benefits in that water applications are scheduled on the basis of plant response to water status. Such irrigation systems require a defined thermal optimum for the crop and while such optimum values have been identified for cotton (Gossypium hirsutum L.) cultivars in the United States, there is no information of this type for cultivars common in Australian production. This paper outlines a threefold approach to determining the optimum temperature (T(opt)) of the commercial Australian cotton cultivar Sicot 70BRF in an Australian production system. It combines the use of a laboratory-based fluorescence assay, field-based net C assimilation rate (A) and stomatal conductance to water vapor (g(s)), and canopy temperature (T(c))-yield relations. The fluorescence assay showed a T(opt) between 28 and 30°C while leaf gas exchange rates peaked at a leaf temperature (Tl) of 29°C. The T(c)-yield relations peaked at 26°C, with yield reductions observed when T(c) > 28°C. We conclude the T(opt) of the Australian upland cotton cultivar Sicot 70BRF to be 28 ± 2°C. This T(opt) will provide valuable information for use in thermal optimum irrigation scheduling systems.

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ∼5000 deg2 survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of ∼24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over ∼27 deg2. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.

Public lands occupied by feral horses in North America are frequently managed for multiple uses with land use conflict occurring among feral horses, livestock, wildlife, and native grassland conservation. The factors affecting habitat use by horses is critical to understand where conflict may be greatest. We related horse presence and abundance to landscape attributes in a GIS to examine habitat preferences using 98 field plots sampled within a portion of the Rocky Mountain Forest Reserve of SW Alberta, Canada. Horse abundance was greatest in grassland and cut block habitats, and lowest in conifer and mixedwood forest. Resource selection probability functions and count models of faecal abundance indicated that horses preferred areas closer to water, with reduced topographic ruggedness, situated farther from forests, and located farther away from primary roads and trails frequented by recreationalists, but closer to small linear features (i.e. cut lines) that may be used as beneficial travel corridors. Horse presence and abundance were closely related to cattle presence during summer, suggesting that both herbivores utilise the same habitats. Estimates of forage biomass removal (44 %) by mid-July were near maximum acceptable levels. In contrast to horse-cattle associations, horses were negatively associated with wild ungulate abundance, although the mechanism behind this remains unclear and warrants further investigation. Our results indicate that feral horses in SW Alberta exhibit complex habitat selection patterns during spring and summer, including overlap in use with livestock. This finding highlights the need to assess and manage herbivore populations consistent with rangeland carrying capacity and the maintenance of range health.

We describe the model for mapping from sky brightness to the digital output of the Dark Energy Camera (DECam) and the algorithms adopted by the Dark Energy Survey (DES) for inverting this model to obtain photometric measures of celestial objects from the raw camera output. This calibration aims for fluxes that are uniform across the camera field of view and across the full angular and temporal span of the DES observations, approaching the accuracy limits set by shot noise for the full dynamic range of DES observations. The DES pipeline incorporates several substantive advances over standard detrending techniques, including principal-components-based sky and fringe subtraction; correction of the “brighter-fatter” nonlinearity; use of internal consistency in on-sky observations to disentangle the influences of quantum efficiency, pixel-size variations, and scattered light in the dome flats; and pixel-by-pixel characterization of instrument spectral response, through combination of internal-consistency constraints with auxiliary calibration data. This article provides conceptual derivations of the detrending/calibration steps, and the procedures for obtaining the necessary calibration data. Other publications will describe the implementation of these concepts for the DES operational pipeline, the detailed methods, and the validation that the techniques can bring DECam photometry and astrometry within ≈2 mmag and ≈3 mas, respectively, of fundamental atmospheric and statistical limits. The DES techniques should be broadly applicable to wide-field imagers.

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ∼5000 deg² survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of ∼24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over ∼27 deg². DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a 5000 deg2 survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of 24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over 27 deg2. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. In this paper, we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.

We present the second public data release (DR2) from the DECam Local Volume Exploration survey (DELVE). DELVE DR2 combines new DECam observations with archival DECam data from the Dark Energy Survey, the DECam Legacy Survey, and other DECam community programs. DELVE DR2 consists of ~160,000 exposures that cover >21,000 deg^2 of the high Galactic latitude (|b| > 10 deg) sky in four broadband optical/near-infrared filters (g, r, i, z). DELVE DR2 provides point-source and automatic aperture photometry for ~2.5 billion astronomical sources with a median 5{\\sigma} point-source depth of g=24.3, r=23.9, i=23.5, and z=22.8 mag. A region of ~17,000 deg^2 has been imaged in all four filters, providing four-band photometric measurements for ~618 million astronomical sources. DELVE DR2 covers more than four times the area of the previous DELVE data release and contains roughly five times as many astronomical objects. DELVE DR2 is publicly available via the NOIRLab Astro Data Lab science platform.

The DECam Local Volume Exploration survey (DELVE) is a 126-night survey program on the 4-m Blanco Telescope at the Cerro Tololo Inter-American Observatory in Chile. DELVE seeks to understand the characteristics of faint satellite galaxies and other resolved stellar substructures over a range of environments in the Local Volume. DELVE will combine new DECam observations with archival DECam data to cover ~15000 deg\\(^2\\) of high-Galactic-latitude (|b| > 10 deg) southern sky to a 5\\(\\sigma\\) depth of g,r,i,z ~ 23.5 mag. In addition, DELVE will cover a region of ~2200 deg\\(^2\\) around the Magellanic Clouds to a depth of g,r,i ~ 24.5 mag and an area of ~135 deg\\(^2\\) around four Magellanic analogs to a depth of g,i ~ 25.5 mag. Here, we present an overview of the DELVE program and progress to date. We also summarize the first DELVE public data release (DELVE DR1), which provides point-source and automatic aperture photometry for ~520 million astronomical sources covering ~5000 deg\\(^2\\) of the southern sky to a 5\\(\\sigma\\) point-source depth of g=24.3, r=23.9, i=23.3, and z=22.8 mag. DELVE DR1 is publicly available via the NOIRLab Astro Data Lab science platform.

We report the discovery of two ultra-faint stellar systems found in early data from the DECam Local Volume Exploration survey (DELVE). The first system, Centaurus I (DELVE J1238-4054), is identified as a resolved overdensity of old and metal-poor stars with a heliocentric distance of \\({\\rm D}_{\\odot} = 116.3_{-0.6}^{+0.6}\\) kpc, a half-light radius of \\(r_h = 2.3_{-0.3}^{+0.4}\\) arcmin, an age of \\(\\tau > 12.85\\) Gyr, a metallicity of \\(Z = 0.0002_{-0.0002}^{+0.0001}\\), and an absolute magnitude of \\(M_V = -5.55_{-0.11}^{+0.11}\\) mag. This characterization is consistent with the population of ultra-faint satellites, and confirmation of this system would make Centaurus I one of the brightest recently discovered ultra-faint dwarf galaxies. Centaurus I is detected in Gaia DR2 with a clear and distinct proper motion signal, confirming that it is a real association of stars distinct from the Milky Way foreground; this is further supported by the clustering of blue horizontal branch stars near the centroid of the system. The second system, DELVE 1 (DELVE J1630-0058), is identified as a resolved overdensity of stars with a heliocentric distance of \\({\\rm D}_{\\odot} = 19.0_{-0.6}^{+0.5} kpc\\), a half-light radius of \\(r_h = 0.97_{-0.17}^{+0.24}\\) arcmin, an age of \\(\\tau = 12.5_{-0.7}^{+1.0}\\) Gyr, a metallicity of \\(Z = 0.0005_{-0.0001}^{+0.0002}\\), and an absolute magnitude of \\(M_V = -0.2_{-0.6}^{+0.8}\\) mag, consistent with the known population of faint halo star clusters. Given the low number of probable member stars at magnitudes accessible with Gaia DR2, a proper motion signal for DELVE 1 is only marginally detected. We compare the spatial position and proper motion of both Centaurus I and DELVE 1 with simulations of the accreted satellite population of the Large Magellanic Cloud (LMC) and find that neither is likely to be associated with the LMC.