Functional Landscape Connectivity Of Greater Sage Grouse Habitat In A Multiple Use Landscape

Maintaining connectivity of sage-grouse habitat is critical to managing sage-grouse populations in the presence of widespread human disturbance. We used an empirical approach to model connectivity of a landscape based on resource selection of free-ranging GPS-collared greater sage-grouse (Centrocercus urophasianus) in a natural gas field in central Wyoming. We analyzed resource selection during three movement states (encamped, traveling, and relocating) and incorporated turning angle to identify features that functioned as barriers or conduits to movement. To illustrate application of the results we used the resource selection model to create spatially-explicit predictive maps identifying areas that generally provided large amounts of high quality ‘movement habitat.’ We found that both males and females selected for vegetation variables at multiple spatial scales. When traveling or relocating, males and females tended to avoid natural gas and oil wells and associated infrastructure and avoided areas with high topographic roughness within 800m. High topographic roughness was a barrier for traveling males. Relocating females were more likely to travel in a straight direction through areas of high road density and steep slopes. The predictive maps validated well using independent GPS location data. These results provide insight into habitat preferences of sage-grouse and can be used for both general and site-specific guidance on identifying habitats preferred or avoided during moderate and long distance movements of sage-grouse. When combined with critical seasonal use maps, e.g., nesting/brooding habitat and winter range, land managers could delineate areas of high value for connectivity of critical seasonal use areas

Efficacy of Manipulating Reproduction of Common Ravens to Conserve Sensitive Prey Species: Three Case Studies

Expansion of human enterprise across western North America has resulted in an increase in availability of anthropogenic resource subsidies for generalist species. This has led to increases in generalists’ population numbers across landscapes that were previously less suitable for their current demographic rates. Of particular concern are growing populations of common ravens (Corvus corax; ravens), because predation by ravens is linked to population declines of sensitive species. Ecosystem managers seek management options for mitigating the adverse effects of raven predation where unsustainable predator–prey conflicts exist. We present 3 case studies examining how manipulating reproductive success of ravens influences demographic rates of 2 sensitive prey species. Two case studies examine impacts of removing raven nests or oiling raven eggs on nest survival of greater sage-grouse (Centrocercus urophasianus; sage-grouse) within Wyoming and the Great Basin of California and Nevada, USA, respectively. The third case study uses Mojave desert tortoise (Gopherus agassizii; tortoise) decoys to examine effects of oiling raven eggs on depredation rates of juvenile tortoises in the Mojave Desert in California. Initial trial years from all 3 case studies were consistent in finding improved vital rates associated with the application of strategies for reducing reproductive success of ravens. Specifically, removal of raven nests resulted in increased nest survival of sage-grouse within treatment areas where predation by ravens was the primary cause of nest failure. In addition, nest survival of sage-grouse and survival of juvenile tortoise decoys was higher following a treatment of oiling the eggs of ravens in their nests at 2 sites within the Great Basin and 4 tortoise conservation areas in the Mojave Desert in California. Along with specialized technologies that can make techniques such as egg-oiling more feasible, these findings support these management practices as important tools for managing ravens, especially in areas where breeding ravens have negative impacts on sensitive prey species

Mercury Information Clearinghouse

The Canadian Electricity Association (CEA) identified a need and contracted the Energy & Environmental Research Center (EERC) to create and maintain an information clearinghouse on global research and development activities related to mercury emissions from coal-fired electric utilities. With the support of CEA, the Center for Air Toxic Metals{reg_sign} (CATM{reg_sign}) Affiliates, and the U.S. Department of Energy (DOE), the EERC developed comprehensive quarterly information updates that provide a detailed assessment of developments in the various areas of mercury monitoring, control, policy, and research. A total of eight topical reports were completed and are summarized and updated in this final CEA quarterly report. The original quarterly reports can be viewed at the CEA Web site (www.ceamercuryprogram.ca). In addition to a comprehensive update of previous mercury-related topics, a review of results from the CEA Mercury Program is provided. Members of Canada's coal-fired electricity generation sector (ATCO Power, EPCOR, Manitoba Hydro, New Brunswick Power, Nova Scotia Power Inc., Ontario Power Generation, SaskPower, and TransAlta) and CEA, have compiled an extensive database of information from stack-, coal-, and ash-sampling activities. Data from this effort are also available at the CEA Web site and have provided critical information for establishing and reviewing a mercury standard for Canada that is protective of environment and public health and is cost-effective. Specific goals outlined for the CEA mercury program included the following: (1) Improve emission inventories and develop management options through an intensive 2-year coal-, ash-, and stack-sampling program; (2) Promote effective stack testing through the development of guidance material and the support of on-site training on the Ontario Hydro method for employees, government representatives, and contractors on an as-needed basis; (3) Strengthen laboratory analytical capabilities through analysis and quality assurance programs; and (4) Create and maintain an information clearinghouse to ensure that all parties can keep informed on global mercury research and development activities

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

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

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

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

Design, Performance and Calibration of the CMS Forward Calorimeter Wedges

We report on the test beam results and calibration methods using charged particles of the CMS Forward Calorimeter (HF). The HF calorimeter covers a large pseudorapidity region (3\l |\eta| \le 5), and is essential for large number of physics channels with missing transverse energy. It is also expected to play a prominent role in the measurement of forward tagging jets in weak boson fusion channels. The HF calorimeter is based on steel absorber with embedded fused-silica-core optical fibers where Cherenkov radiation forms the basis of signal generation. Thus, the detector is essentially sensitive only to the electromagnetic shower core and is highly non-compensating (e/h \approx 5). This feature is also manifest in narrow and relatively short showers compared to similar calorimeters based on ionization. The choice of fused-silica optical fibers as active material is dictated by its exceptional radiation hardness. The electromagnetic energy resolution is dominated by photoelectron statistics and can be expressed in the customary form as a/\sqrt{E} + b. The stochastic term a is 198% and the constant term b is 9%. The hadronic energy resolution is largely determined by the fluctuations in the neutral pion production in showers, and when it is expressed as in the electromagnetic case, a = 280% and b = 11%

Identifying and Prioritizing Greater Sage-Grouse Nesting and Brood-Rearing Habitat for Conservation in Human-Modified Landscapes

BACKGROUND: Balancing animal conservation and human use of the landscape is an ongoing scientific and practical challenge throughout the world. We investigated reproductive success in female greater sage-grouse (Centrocercus urophasianus) relative to seasonal patterns of resource selection, with the larger goal of developing a spatially-explicit framework for managing human activity and sage-grouse conservation at the landscape level. METHODOLOGY/PRINCIPAL FINDINGS: We integrated field-observation, Global Positioning Systems telemetry, and statistical modeling to quantify the spatial pattern of occurrence and risk during nesting and brood-rearing. We linked occurrence and risk models to provide spatially-explicit indices of habitat-performance relationships. As part of the analysis, we offer novel biological information on resource selection during egg-laying, incubation, and night. The spatial pattern of occurrence during all reproductive phases was driven largely by selection or avoidance of terrain features and vegetation, with little variation explained by anthropogenic features. Specifically, sage-grouse consistently avoided rough terrain, selected for moderate shrub cover at the patch level (within 90 m(2)), and selected for mesic habitat in mid and late brood-rearing phases. In contrast, risk of nest and brood failure was structured by proximity to anthropogenic features including natural gas wells and human-created mesic areas, as well as vegetation features such as shrub cover. CONCLUSIONS/SIGNIFICANCE: Risk in this and perhaps other human-modified landscapes is a top-down (i.e., human-mediated) process that would most effectively be minimized by developing a better understanding of specific mechanisms (e.g., predator subsidization) driving observed patterns, and using habitat-performance indices such as those developed herein for spatially-explicit guidance of conservation intervention. Working under the hypothesis that industrial activity structures risk by enhancing predator abundance or effectiveness, we offer specific recommendations for maintaining high-performance habitat and reducing low-performance habitat, particularly relative to the nesting phase, by managing key high-risk anthropogenic features such as industrial infrastructure and water developments