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  • 1
    Publication Date: 2015-12-16
    Description: ABSTRACT Many tropical islands have limited water resources with historically increasing demand, all potentially affected by a changing climate. The effects of climate change on island hydrology are difficult to model due to steep local precipitation gradients and sparse data. This work uses 10 statistically downscaled general circulation models (GCMs) under two greenhouse gas emission scenarios to evaluate the uncertainty propagated from GCMs in projecting the effects of climate change on water resources in a tropical island system. The assessment is conducted using a previously configured hydrologic model, the Precipitation Runoff Modelling System (PRMS) for Puerto Rico. Projected climate data and their modelled hydrologic variables versus historical measurements and their modelled hydrologic variables are found to have empirical distribution functions that are statistically different with less than 1 year of daily data aggregation. Thus, only annual averages of the projected hydrologic variables are employed as completely bias-corrected model outputs. The magnitude of the projected total flow decreases in the four regions covering Puerto Rico, but with a large range of uncertainty depending on the makeup of the GCM ensemble. The multi-model mean projected total flow decreases by 49–88% of historical amounts from the 1960s to the 2090s for the high emissions scenarios and by 39–79% for the low emissions scenarios. Subsurface flow contributions decreased the least and groundwater flow contributions decreased the most across the island. At locations critical to water supply for human use, projected streamflow is shown to decrease substantially below projected withdrawals by 2099.
    Print ISSN: 0899-8418
    Electronic ISSN: 1097-0088
    Topics: Geosciences , Physics
    Published by Wiley
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  • 2
    Publication Date: 2013-03-23
    Description: Glycosylated alpha-dystroglycan (alpha-DG) serves as cellular entry receptor for multiple pathogens, and defects in its glycosylation cause hereditary Walker-Warburg syndrome (WWS). At least eight proteins are critical to glycosylate alpha-DG, but many genes mutated in WWS remain unknown. To identify modifiers of alpha-DG, we performed a haploid screen for Lassa virus entry, a hemorrhagic fever virus causing thousands of deaths annually that hijacks glycosylated alpha-DG to enter cells. In complementary screens, we profiled cells for absence of alpha-DG carbohydrate chains or biochemically related glycans. This revealed virus host factors and a suite of glycosylation units, including all known Walker-Warburg genes and five additional factors critical for the modification of alpha-DG. Our findings accentuate the complexity of this posttranslational feature and point out genes defective in dystroglycanopathies.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3919138/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3919138/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Jae, Lucas T -- Raaben, Matthijs -- Riemersma, Moniek -- van Beusekom, Ellen -- Blomen, Vincent A -- Velds, Arno -- Kerkhoven, Ron M -- Carette, Jan E -- Topaloglu, Haluk -- Meinecke, Peter -- Wessels, Marja W -- Lefeber, Dirk J -- Whelan, Sean P -- van Bokhoven, Hans -- Brummelkamp, Thijn R -- AI057159/AI/NIAID NIH HHS/ -- AI081842/AI/NIAID NIH HHS/ -- R01 AI081842/AI/NIAID NIH HHS/ -- U54 AI057159/AI/NIAID NIH HHS/ -- New York, N.Y. -- Science. 2013 Apr 26;340(6131):479-83. doi: 10.1126/science.1233675. Epub 2013 Mar 21.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam, Netherlands.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/23519211" target="_blank"〉PubMed〈/a〉
    Keywords: Amino Acid Sequence ; Cell Line ; Dystroglycans/*metabolism ; Female ; Glycosylation ; Haploidy ; Host-Pathogen Interactions/*genetics ; Humans ; Infant ; Lassa Fever/*genetics/virology ; Lassa virus/*physiology ; Male ; Membrane Proteins/*genetics ; Molecular Sequence Data ; Mutation ; Pedigree ; Proteome/*metabolism ; *Virus Internalization ; Walker-Warburg Syndrome/*genetics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 3
    Publication Date: 2018-09-01
    Description: Remote Sensing, Vol. 10, Pages 1386: Hurricane Maria in the U.S. Caribbean: Disturbance Forces, Variation of Effects, and Implications for Future Storms Remote Sensing doi: 10.3390/rs10091386 Authors: Ashley E. Van Beusekom Nora L. Álvarez-Berríos William A. Gould Maya Quiñones Grizelle González The impact of Hurricane Maria on the U.S. Caribbean was used to study the causes of remotely-sensed spatial variation in the effects of (1) vegetation index loss and (2) landslide occurrence. The vegetation index is a measure of canopy ‘greenness’, a combination of leaf chlorophyll, leaf area, canopy cover and structure. A generalized linear model was made for each kind of effect, using idealized maps of the hurricane forces, along with three landscape characteristics that were significantly associated. In each model, one of these characteristics was forest fragmentation, and another was a measure of disturbance-propensity. For the greenness loss model, the hurricane force was wind, the disturbance-propensity measure was initial greenness, and the third landscape characteristic was fraction forest cover. For the landslide occurrence model, the hurricane force was rain, the disturbance-propensity measure was amount of land slope, and the third landscape characteristic was soil clay content. The model of greenness loss had a pseudo R2 of 0.73 and showed the U.S. Caribbean lost 31% of its initial greenness from the hurricane, with 51% lost from the initial in the Luquillo Experimental Forest (LEF) from Hurricane Maria along with Hurricane Irma. More greenness disturbance was seen in areas with less wind sheltering, higher elevation and topographic sides. The model of landslide occurrence had a pseudo R2 of 0.53 and showed the U.S. Caribbean had 34% of its area and 52% of the LEF area with a landslide density of at least one in 1 km2 from Hurricane Maria. Four experiments with parameters from previous storms of wind speed, storm duration, rainfall, and forest structure over the same storm path and topographic landscape were run as examples of possible future scenarios. While intensity of the storm makes by far the largest scenario difference, forest fragmentation makes a sizable difference especially in vulnerable areas of high clay content or high wind susceptibility. This study showed the utility of simple hurricane force calculations connected with landscape characteristics and remote-sensing data to determine forest susceptibility to hurricane effects.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by MDPI Publishing
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  • 4
    Publication Date: 2016-10-18
    Description: A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense, but still relies on physical principles over empirical relations as much as is feasible while maintaining model usability. PRMSglacier is validated on two basins in Alaska, Wolverine and Gulkana Glacier basin, which have been studied since 1966 and have a substantial amount of data with which to test model performance over a long period of time covering a wide range of climatic and hydrologic conditions. When error in field measurements is considered, the Nash-Sutcliffe efficiencies of streamflow are 0.87 and 0.86, the absolute bias fractions of the winter mass balance simulations are 0.10 and 0.08, and the absolute bias fractions of the summer mass balances are 0.01 and 0.03, all computed over 42 years for the Wolverine and Gulkana Glacier basins, respectively. Without taking into account measurement error, the values are still within the range achieved by the more computationally expensive codes tested over shorter time periods.
    Print ISSN: 0148-0227
    Topics: Geosciences , Physics
    Published by Wiley on behalf of American Geophysical Union (AGU).
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  • 5
    Publication Date: 2013-04-02
    Description: Several known or putative glycosyltransferases are required for the synthesis of laminin-binding glycans on alpha-dystroglycan (αDG), including POMT1, POMT2, POMGnT1, LARGE, Fukutin, FKRP, ISPD and GTDC2. Mutations in these glycosyltransferase genes result in defective αDG glycosylation and reduced ligand binding by αDG causing a clinically heterogeneous group of congenital muscular dystrophies, commonly referred to as dystroglycanopathies. The most severe clinical form, Walker–Warburg syndrome (WWS), is characterized by congenital muscular dystrophy and severe neurological and ophthalmological defects. Here, we report two homozygous missense mutations in the β-1,3- N -acetylglucosaminyltransferase 1 ( B3GNT1 ) gene in a family affected with WWS. Functional studies confirmed the pathogenicity of the mutations. First, expression of wild-type but not mutant B3GNT1 in human prostate cancer (PC3) cells led to increased levels of αDG glycosylation. Second, morpholino knockdown of the zebrafish b3gnt1 orthologue caused characteristic muscular defects and reduced αDG glycosylation. These functional studies identify an important role of B3GNT1 in the synthesis of the uncharacterized laminin-binding glycan of αDG and implicate B3GNT1 as a novel causative gene for WWS.
    Print ISSN: 0964-6906
    Electronic ISSN: 1460-2083
    Topics: Biology , Medicine
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  • 6
    Publication Date: 2013-03-21
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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