8 research outputs found

    Causal Connections between Water Quality and Land Use in a Rural Tropical Island Watershed: Rural Tropical Island Watershed Analysis

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    We examined associations between riparian canopy cover, presence or absence of cattle, rainfall, solar radiation, month of year, dissolved oxygen, turbidity, salinity, and Enterococcus concentrations in riparian surface soils with Enterococcus geometric mean in-stream water concentrations at Waipā watershed on the north side of the Hawaiian island Kaua’i. Each 1% decrease in riparian canopy cover was associated with a 4.6 most probable number (MPN)/100 ml increase of the geometric mean of Enterococcus in stream water (P < 0.05). Each unit decrease in salinity (ppt) was associated with an increase of Enterococcus by 68.2 MPN/100 ml in-stream water geometric mean concentrations (P < 0.05). Month of year was also associated with increases in stream water Enterococcus geometric mean concentrations (P < 0.05). Reducing riparian canopy cover is associated with Enterococcus increases in stream water, suggesting that decreasing riparian vegetation density could increase fecal bacteria surface runoff

    From Data to Software to Science with the Rubin Observatory LSST

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    The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.Comment: White paper from "From Data to Software to Science with the Rubin Observatory LSST" worksho

    From Data to Software to Science with the Rubin Observatory LSST

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    editorial reviewedThe Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science

    Characterizing riparian ecosystems (plants, soil, and water) of Waipā, Kauaʻi of the Hawaiian Islands

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    Thesis (M.S.)--University of Hawaii at Manoa, 2006.Includes bibliographical references.x, 209 leaves, bound ill., maps 29 c
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