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Search: WFRF:(Elder Kelly)

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1.
  • Brown, Kevin M., et al. (author)
  • Common sequence variants on 20q11.22 confer melanoma susceptibility
  • 2008
  • In: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 40:7, s. 838-840
  • Journal article (peer-reviewed)abstract
    • We conducted a genome-wide association pooling study for cutaneous melanoma and performed validation in samples totaling 2,019 cases and 2,105 controls. Using pooling, we identified a new melanoma risk locus on chromosome 20 (rs910873 and rs1885120), with replication in two further samples (combined P < 1 x 10(-15)). The per allele odds ratio was 1.75 (1.53, 2.01), with evidence for stronger association in early-onset cases.
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2.
  • Essery, Richard, et al. (author)
  • An Evaluation of Forest Snow Process Simulations
  • 2009
  • In: Bulletin of The American Meteorological Society - (BAMS). - : American Meteorological Society. - 0003-0007 .- 1520-0477. ; 90:8, s. 1120-
  • Journal article (peer-reviewed)abstract
    • The Northern Hemisphere has large areas that are forested and seasonally snow covered. Compared with open areas, forest canopies strongly influence interactions between the atmosphere and snow on the ground by sheltering the snow from wind and solar radiation and by intercepting falling snow; these influences have important consequences for the meteorology, hydrology, and ecology of forests. Many of the land surface models used in meteorological and hydrological forecasting now include representations of canopy snow processes, but these have not been widely tested in comparison with observations. Phase 2 of the Snow Model Intercomparison Project (SnowMIP2) was therefore designed as an intercomparison of surface mass and energy balance simulations for snow in forested areas. Model forcing and calibration data for sites with paired forested and open plots were supplied to modeling groups. Participants in 11 countries contributed output from 33 models, and the results are published here for sites in Canada, the United States, and Switzerland. On average, the models perform fairly well in simulating snow accumulation and ablation, although there is a wide intermodal spread and a tendency to underestimate differences in snow mass between open and forested areas. Most models capture the large differences in surface albedos and temperatures between forest canopies and open snow well. There is, however, a strong tendency for models to underestimate soil temperature under snow, particularly for forest sites, and this would have large consequences for simulations of runoff and biological processes in the soil.
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3.
  • Hsiang, Allison (author)
  • AutoMorph: Accelerating morphometrics with automated 2D and 3D image processing and shape extraction
  • 2017
  • In: Methods in Ecology and Evolution. - 2041-210X.
  • Journal article (peer-reviewed)abstract
    • Large-scale, comparative studies of morphological variation are rare due to the time-intensive nature of shape quantification. This data gap is important to address, as intraspecific and interspecific morphological variation underpins and reflects ecological and evolutionary processes.Here, we detail a novel software package, AutoMorph, for high-throughput object and shape extraction. AutoMorph can batch image many types of organisms (e.g. foraminifera, molluscs and fish teeth), allowing for rapid generation of assemblage- scale morphological data.We used AutoMorph to image and generate 2D and 3D morphological data for >100,000 marine microfossils in about a year. Our collaborators have used AutoMorph to process >12,000 patellogastropod shells and >50,000 fish teeth.AutoMorph allows users to rapidly produce large amounts of morphological data, facilitating community-scale evolutionary and ecological studies. To hasten the adoption of automated approaches, we have made AutoMorph freely available and open source. AutoMorph runs on all UNIX-like systems; future versions will run across all platforms. 
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5.
  • Rutter, Nick, et al. (author)
  • Evaluation of forest snow processes models (SnowMIP2)
  • 2009
  • In: Journal of Geophysical Research. - : American Geophysical Union (AGU). - 0148-0227 .- 2156-2202. ; 114:6
  • Journal article (peer-reviewed)abstract
    • Thirty-three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to two winter snow seasons. Modeled estimates of snow water equivalent (SWE) or depth were compared to observations at forest and open sites at each location. Precipitation phase and duration of above-freezing air temperatures are shown to be major influences on divergence and convergence of modeled estimates of the subcanopy snowpack. When models are considered collectively at all locations, comparisons with observations show that it is harder to model SWE at forested sites than open sites. There is no universal "best'' model for all sites or locations, but comparison of the consistency of individual model performances relative to one another at different sites shows that there is less consistency at forest sites than open sites, and even less consistency between forest and open sites in the same year. A good performance by a model at a forest site is therefore unlikely to mean a good model performance by the same model at an open site (and vice versa). Calibration of models at forest sites provides lower errors than uncalibrated models at three out of four locations. However, benefits of calibration do not translate to subsequent years, and benefits gained by models calibrated for forest snow processes are not translated to open conditions.
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