A FUTURISTIC LOOK AT THE USE OF GRAZED FORAGES IN THE WESTERN UNITED STATES

Scenario analysis was used to develop scenarios the grazed forage industry in the western U.S. will most likely face over the next several decades. Five major factors were identified as being most consequential. Scenarios indicated that livestock use of grazing lands will most likely decline while wildlife use will increase.Land Economics/Use, Livestock Production/Industries,

AN EVALUATION OF THE PRIA GRAZING FEE FORMULA

The federal grazing fee is currently set using the Public Rangeland Improvement Act (PRIA) fee formula established in 1978 and modified in 1986. The formula is adjusted annually using indices of private land grazing lease rates (Forage Value Index, FVI), prices received for beef cattle (Beef Cattle Price Index, BCPI), and costs of beef production (Prices Paid Index, PPI). The FVI tracks price movement in the private forage market and was the only index originally proposed to be included in the fee formula. Public land ranchers and an Interdepartmental Grazing Fee Technical Committee assigned to study grazing fee alternatives in the 1960s questioned the ability of the FVI to account for short-term demand, supply, and price equilibrium, and, for this reason, the BCPI and PPI were added to the fee formula. Over 30 years of data are now available to evaluate whether adding the BCPI and PPI did, in fact, help explain short-term market fluctuations. This analysis shows, as earlier studies did, that, if tracking the private forage market is the primary objective, then the fee formula should have included only the FVI. Including the BCPI and, especially, the PPI has caused calculated grazing fees to fall further and further behind private land lease rates. Had the $1.23 base fee in the PRIA formula been indexed by only the FVI, the federal grazing fee would have been$3.84/AUM instead of $1.35/AUM in 2000. It is time to consider the feasibility of a competitive bid system for public lands, or, at the very least, adopt a new fee formula that generates more equitable grazing fees.Land Economics/Use,

Deep Imaging of AXJ2019+112: The Luminosity of a ``Dark Cluster''

We detect a distant cluster of galaxies centered on the QSO lens and luminous X-ray source AXJ2019+112, a.k.a. ``The Dark Cluster'' (Hattori et al 1997). Using deep V,I Keck images and wide-field K_s imaging from the NTT, a tight red sequence of galaxies is identified within a radius of 0.2 h^{-1} Mpc of the known z=1.01 elliptical lensing galaxy. The sequence, which includes the central elliptical galaxy, has a slope in good agreement with the model predictions of Kodama et al (1998) for z~1. We estimate the integrated rest-frame luminosity of the cluster to be L_V > 3.2 x 10^{11}h^{-2}L_{\sun} (after accounting for significant extinction at the low latitude of this field), more than an order of magnitude higher than previous estimates. The central region of the cluster is deconvolved using the technique of Magain, Courbin & Sohy (1998), revealing a thick central arc coincident with an extended radio source. All the observed lensing features are readily explained by differential magnification of a radio loud AGN by a shallow elliptical potential. The QSO must lie just outside the diamond caustic, producing two images, and the arc is a highly magnified image formed from a region close to the center of the host galaxy, projecting inside the caustic. The mass--to--light ratio within an aperture of 0.4 h ^{-1} Mpc is M_x/L_V= 224^{+112}_{-78}h(M/L_V)_{\sun}, using the X-ray temperature. The strong lens model yields a compatible value, M/L_V= 372^{+94}_{-94}h(M/L_V)_{\sun}, whereas an independent weak lensing analysis sets an upper limit of M/L_V <520 h(M/L_V)_{\sun}, typical of massive clusters.Comment: AAS Latex format, 24 pages, 9 figures. Fig 1a,b available at http://astro.berkeley.edu/~benitezn/cluster.html . Submitted to ApJ on August 15t

Bunching behaviour in housed dairy cows at higher ambient temperatures.

Bunching behavior in cattle may occur for several reasons including enabling social interactions, a response to stress or danger, or due to shared interest in resources such as feeding or watering areas. There is evidence in pasture grazed cattle that bunching may occur more frequently at higher ambient temperatures, possibly due to sharing of fly-load or to seek shade from the direct sun under heat stress conditions. Here we demonstrate how bunching behavior is associated with higher ambient temperatures in a barn-housed UK dairy herd. A real-time local positioning system (RTLS) was used, as part of a precision livestock farming (PLF) approach, to track the spatial position and activity of a commercial dairy herd (c100 cows) in a freestall barn continuously at high temporal resolution for 4 mo between August and November 2014. Bunching was determined using 4 different spatial measures determined on an hourly basis: herd full and core range size, mean herd inter-cow distance (ICD), and mean herd nearest neighbor distance (NND). For hourly mean ambient temperatures above 20°C, the herd showed higher bunching behavior with increasing ambient temperature (i.e., reduced full and core range size, ICD, and NND). Aggregated space-use intensity was found to positively correlate with localized variations in temperature across the barn (as measured by animal mounted sensors), but the level of correlation decreased at higher ambient barn temperatures. Bunching behavior may increase localized temperatures experienced by individuals and hence may be a maladaptive behavioral response in housed dairy cattle, which are known to suffer heat stress at higher temperatures. Our study is the first to use high-resolution positional data to provide evidence of associations between bunching behavior and higher ambient temperatures for a barn-housed dairy herd in a temperate region (UK). Further studies are needed to explore the exact mechanisms for this response to inform both welfare and production management

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment