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  • 1
    Publication Date: 2016-01-20
    Description: Congenital heart disease (CHD) patients have an increased prevalence of extracardiac congenital anomalies (CAs) and risk of neurodevelopmental disabilities (NDDs). Exome sequencing of 1213 CHD parent-offspring trios identified an excess of protein-damaging de novo mutations, especially in genes highly expressed in the developing heart and brain. These mutations accounted for 20% of patients with CHD, NDD, and CA but only 2% of patients with isolated CHD. Mutations altered genes involved in morphogenesis, chromatin modification, and transcriptional regulation, including multiple mutations in RBFOX2, a regulator of mRNA splicing. Genes mutated in other cohorts examined for NDD were enriched in CHD cases, particularly those with coexisting NDD. These findings reveal shared genetic contributions to CHD, NDD, and CA and provide opportunities for improved prognostic assessment and early therapeutic intervention in CHD patients.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Homsy, Jason -- Zaidi, Samir -- Shen, Yufeng -- Ware, James S -- Samocha, Kaitlin E -- Karczewski, Konrad J -- DePalma, Steven R -- McKean, David -- Wakimoto, Hiroko -- Gorham, Josh -- Jin, Sheng Chih -- Deanfield, John -- Giardini, Alessandro -- Porter, George A Jr -- Kim, Richard -- Bilguvar, Kaya -- Lopez-Giraldez, Francesc -- Tikhonova, Irina -- Mane, Shrikant -- Romano-Adesman, Angela -- Qi, Hongjian -- Vardarajan, Badri -- Ma, Lijiang -- Daly, Mark -- Roberts, Amy E -- Russell, Mark W -- Mital, Seema -- Newburger, Jane W -- Gaynor, J William -- Breitbart, Roger E -- Iossifov, Ivan -- Ronemus, Michael -- Sanders, Stephan J -- Kaltman, Jonathan R -- Seidman, Jonathan G -- Brueckner, Martina -- Gelb, Bruce D -- Goldmuntz, Elizabeth -- Lifton, Richard P -- Seidman, Christine E -- Chung, Wendy K -- T32 HL007208/HL/NHLBI NIH HHS/ -- Arthritis Research UK/United Kingdom -- British Heart Foundation/United Kingdom -- Department of Health/United Kingdom -- Howard Hughes Medical Institute/ -- Wellcome Trust/United Kingdom -- New York, N.Y. -- Science. 2015 Dec 4;350(6265):1262-6. doi: 10.1126/science.aac9396.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Genetics, Harvard Medical School, Boston, MA, USA. Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA. ; Department of Genetics, Yale University School of Medicine, New Haven, CT, USA. ; Departments of Systems Biology and Biomedical Informatics, Columbia University Medical Center, New York, NY, USA. ; Department of Genetics, Harvard Medical School, Boston, MA, USA. NIHR Cardiovascular Biomedical Research Unit at Royal Brompton & Harefield NHS Foundation and Trust and Imperial College London, London, UK. National Heart & Lung Institute, Imperial College London, London, UK. ; Department of Genetics, Harvard Medical School, Boston, MA, USA. Analytical and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston MA, USA. ; Department of Genetics, Harvard Medical School, Boston, MA, USA. Howard Hughes Medical Institute, Harvard University, Boston, MA, USA. ; Department of Genetics, Harvard Medical School, Boston, MA, USA. ; Department of Cardiology, University College London and Great Ormond Street Hospital, London, UK. ; Department of Pediatrics, University of Rochester Medical Center, The School of Medicine and Dentistry, Rochester, NY, USA. ; Section of Cardiothoracic Surgery, University of Southern California Keck School of Medicine, Los Angeles, CA, USA. ; Department of Genetics, Yale University School of Medicine, New Haven, CT, USA. Yale Center for Genome Analysis, Yale University, New Haven, CT, USA. ; Yale Center for Genome Analysis, Yale University, New Haven, CT, USA. ; Steven and Alexandra Cohen Children's Medical Center of New York, New Hyde Park, NY, USA. ; Departments of Systems Biology and Biomedical Informatics, Columbia University Medical Center, New York, NY, USA. Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA. ; Department of Neurology, Columbia University Medical Center, New York, NY, USA. ; Department of Pediatrics, Columbia University Medical Center, New York, NY, USA. ; Department of Cardiology, Children's Hospital Boston, Boston, MA, USA. ; Division of Pediatric Cardiology, University of Michigan, Ann Arbor, MI, USA. ; Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada. ; Department of Cardiology, Boston Children's Hospital, Boston, MA, USA. ; Department of Pediatric Cardiac Surgery, The Children's Hospital of Philadelphia, Philadelphia, PA, USA. ; Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. ; Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA. ; Heart Development and Structural Diseases Branch, Division of Cardiovascular Sciences, NHLBI/NIH, Bethesda, MD, USA. ; Department of Genetics, Yale University School of Medicine, New Haven, CT, USA. bruce.gelb@mssm.edu goldmuntz@email.chop.edu martina.brueckner@yale.edu richard.lifton@yale.edu cseidman@genetics.med.harvard.edu wkc15@cumc.columbia.edu. ; Mindich Child Health and Development Institute and Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA. bruce.gelb@mssm.edu goldmuntz@email.chop.edu martina.brueckner@yale.edu richard.lifton@yale.edu cseidman@genetics.med.harvard.edu wkc15@cumc.columbia.edu. ; Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Division of Cardiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA. bruce.gelb@mssm.edu goldmuntz@email.chop.edu martina.brueckner@yale.edu richard.lifton@yale.edu cseidman@genetics.med.harvard.edu wkc15@cumc.columbia.edu. ; Department of Genetics, Yale University School of Medicine, New Haven, CT, USA. Howard Hughes Medical Institute, Yale University, New Haven, CT, USA. bruce.gelb@mssm.edu goldmuntz@email.chop.edu martina.brueckner@yale.edu richard.lifton@yale.edu cseidman@genetics.med.harvard.edu wkc15@cumc.columbia.edu. ; Department of Genetics, Harvard Medical School, Boston, MA, USA. Howard Hughes Medical Institute, Harvard University, Boston, MA, USA. Cardiovascular Division, Brigham & Women's Hospital, Harvard University, Boston, MA, USA. bruce.gelb@mssm.edu goldmuntz@email.chop.edu martina.brueckner@yale.edu richard.lifton@yale.edu cseidman@genetics.med.harvard.edu wkc15@cumc.columbia.edu. ; Departments of Pediatrics and Medicine, Columbia University Medical Center, New York, NY, USA. bruce.gelb@mssm.edu goldmuntz@email.chop.edu martina.brueckner@yale.edu richard.lifton@yale.edu cseidman@genetics.med.harvard.edu wkc15@cumc.columbia.edu.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26785492" target="_blank"〉PubMed〈/a〉
    Keywords: Brain/abnormalities/metabolism ; Child ; Congenital Abnormalities/genetics ; Exome/genetics ; Heart Defects, Congenital/*diagnosis/*genetics ; Humans ; Mutation ; Nervous System Malformations/*genetics ; Neurogenesis/*genetics ; Prognosis ; RNA Splicing/genetics ; RNA, Messenger/genetics ; RNA-Binding Proteins/genetics ; Repressor Proteins/genetics ; Transcription, Genetic
    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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  • 2
    Publication Date: 2016-02-26
    Description: 5-Methylthioadenosine phosphorylase (MTAP) is a key enzyme in the methionine salvage pathway. The MTAP gene is frequently deleted in human cancers because of its chromosomal proximity to the tumor suppressor gene CDKN2A. By interrogating data from a large-scale short hairpin RNA-mediated screen across 390 cancer cell line models, we found that the viability of MTAP-deficient cancer cells is impaired by depletion of the protein arginine methyltransferase PRMT5. MTAP-deleted cells accumulate the metabolite methylthioadenosine (MTA), which we found to inhibit PRMT5 methyltransferase activity. Deletion of MTAP in MTAP-proficient cells rendered them sensitive to PRMT5 depletion. Conversely, reconstitution of MTAP in an MTAP-deficient cell line rescued PRMT5 dependence. Thus, MTA accumulation in MTAP-deleted cancers creates a hypomorphic PRMT5 state that is selectively sensitized toward further PRMT5 inhibition. Inhibitors of PRMT5 that leverage this dysregulated metabolic state merit further investigation as a potential therapy for MTAP/CDKN2A-deleted tumors.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Mavrakis, Konstantinos J -- McDonald, E Robert 3rd -- Schlabach, Michael R -- Billy, Eric -- Hoffman, Gregory R -- deWeck, Antoine -- Ruddy, David A -- Venkatesan, Kavitha -- Yu, Jianjun -- McAllister, Gregg -- Stump, Mark -- deBeaumont, Rosalie -- Ho, Samuel -- Yue, Yingzi -- Liu, Yue -- Yan-Neale, Yan -- Yang, Guizhi -- Lin, Fallon -- Yin, Hong -- Gao, Hui -- Kipp, D Randal -- Zhao, Songping -- McNamara, Joshua T -- Sprague, Elizabeth R -- Zheng, Bing -- Lin, Ying -- Cho, Young Shin -- Gu, Justin -- Crawford, Kenneth -- Ciccone, David -- Vitari, Alberto C -- Lai, Albert -- Capka, Vladimir -- Hurov, Kristen -- Porter, Jeffery A -- Tallarico, John -- Mickanin, Craig -- Lees, Emma -- Pagliarini, Raymond -- Keen, Nicholas -- Schmelzle, Tobias -- Hofmann, Francesco -- Stegmeier, Frank -- Sellers, William R -- New York, N.Y. -- Science. 2016 Mar 11;351(6278):1208-13. doi: 10.1126/science.aad5944. Epub 2016 Feb 11.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Novartis Institutes for Biomedical Research, Cambridge, MA 02139, USA. ; Novartis Institutes for Biomedical Research, Basel CH-4002, Switzerland. ; Novartis Institutes for Biomedical Research, Emeryville, CA 94608, USA. ; China Novartis Institutes for Biomedical Research, Shanghai 201203, China. ; Novartis Institutes for Biomedical Research, Cambridge, MA 02139, USA. william.sellers@novartis.com fstegmeier@ksqtx.com.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26912361" target="_blank"〉PubMed〈/a〉
    Keywords: Cell Line, Tumor ; Cell Survival ; Cyclin-Dependent Kinase Inhibitor p16/genetics/*metabolism ; Deoxyadenosines/metabolism ; Gene Deletion ; Humans ; Methionine/*metabolism ; Neoplasms/drug therapy/genetics/*metabolism ; Protein-Arginine N-Methyltransferases/genetics/*metabolism ; Purine-Nucleoside Phosphorylase/genetics/*metabolism ; RNA, Small Interfering/genetics ; Thionucleosides/metabolism
    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: 2016-02-06
    Description: SH3 and multiple ankyrin repeat domains 3 (SHANK3) haploinsufficiency is causative for the neurological features of Phelan-McDermid syndrome (PMDS), including a high risk of autism spectrum disorder (ASD). We used unbiased, quantitative proteomics to identify changes in the phosphoproteome of Shank3-deficient neurons. Down-regulation of protein kinase B (PKB/Akt)-mammalian target of rapamycin complex 1 (mTORC1) signaling resulted from enhanced phosphorylation and activation of serine/threonine protein phosphatase 2A (PP2A) regulatory subunit, B56beta, due to increased steady-state levels of its kinase, Cdc2-like kinase 2 (CLK2). Pharmacological and genetic activation of Akt or inhibition of CLK2 relieved synaptic deficits in Shank3-deficient and PMDS patient-derived neurons. CLK2 inhibition also restored normal sociability in a Shank3-deficient mouse model. Our study thereby provides a novel mechanistic and potentially therapeutic understanding of deregulated signaling downstream of Shank3 deficiency.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Bidinosti, Michael -- Botta, Paolo -- Kruttner, Sebastian -- Proenca, Catia C -- Stoehr, Natacha -- Bernhard, Mario -- Fruh, Isabelle -- Mueller, Matthias -- Bonenfant, Debora -- Voshol, Hans -- Carbone, Walter -- Neal, Sarah J -- McTighe, Stephanie M -- Roma, Guglielmo -- Dolmetsch, Ricardo E -- Porter, Jeffrey A -- Caroni, Pico -- Bouwmeester, Tewis -- Luthi, Andreas -- Galimberti, Ivan -- New York, N.Y. -- Science. 2016 Mar 11;351(6278):1199-203. doi: 10.1126/science.aad5487. Epub 2016 Feb 4.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Developmental Molecular Pathways, Novartis Institutes for Biomedical Research, Basel, Switzerland. ; Friedrich Miescher Institute, Basel, Switzerland. ; Analytical Sciences and Imaging, Novartis Institutes for Biomedical Research, Basel, Switzerland. ; Neuroscience, Novartis Institutes for Biomedical Research, Cambridge, USA. ; Developmental Molecular Pathways, Novartis Institutes for Biomedical Research, Basel, Switzerland. ivan.galimberti@novartis.com.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26847545" target="_blank"〉PubMed〈/a〉
    Keywords: Amino Acid Sequence ; Animals ; Autism Spectrum Disorder/*drug therapy/enzymology/genetics ; Chromosome Deletion ; Chromosome Disorders/genetics ; Chromosomes, Human, Pair 22/genetics ; Disease Models, Animal ; Down-Regulation ; Gene Knockdown Techniques ; Humans ; Insulin-Like Growth Factor I/metabolism ; Mice ; Molecular Sequence Data ; Multiprotein Complexes/metabolism ; Nerve Tissue Proteins/*genetics ; Neurons/enzymology ; Phosphorylation ; Protein Phosphatase 2/metabolism ; Protein-Serine-Threonine Kinases/*antagonists & inhibitors/metabolism ; Protein-Tyrosine Kinases/*antagonists & inhibitors/metabolism ; Proteomics ; Proto-Oncogene Proteins c-akt/genetics/metabolism ; Rats ; Signal Transduction ; TOR Serine-Threonine Kinases/metabolism
    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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  • 4
    Publication Date: 2015-01-09
    Description: Yeasts, which have been a component of the human diet for at least 7,000 years, possess an elaborate cell wall alpha-mannan. The influence of yeast mannan on the ecology of the human microbiota is unknown. Here we show that yeast alpha-mannan is a viable food source for the Gram-negative bacterium Bacteroides thetaiotaomicron, a dominant member of the microbiota. Detailed biochemical analysis and targeted gene disruption studies support a model whereby limited cleavage of alpha-mannan on the surface generates large oligosaccharides that are subsequently depolymerized to mannose by the action of periplasmic enzymes. Co-culturing studies showed that metabolism of yeast mannan by B. thetaiotaomicron presents a 'selfish' model for the catabolism of this difficult to breakdown polysaccharide. Genomic comparison with B. thetaiotaomicron in conjunction with cell culture studies show that a cohort of highly successful members of the microbiota has evolved to consume sterically-restricted yeast glycans, an adaptation that may reflect the incorporation of eukaryotic microorganisms into the human diet.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Cuskin, Fiona -- Lowe, Elisabeth C -- Temple, Max J -- Zhu, Yanping -- Cameron, Elizabeth A -- Pudlo, Nicholas A -- Porter, Nathan T -- Urs, Karthik -- Thompson, Andrew J -- Cartmell, Alan -- Rogowski, Artur -- Hamilton, Brian S -- Chen, Rui -- Tolbert, Thomas J -- Piens, Kathleen -- Bracke, Debby -- Vervecken, Wouter -- Hakki, Zalihe -- Speciale, Gaetano -- Munoz-Munoz, Jose L -- Day, Andrew -- Pena, Maria J -- McLean, Richard -- Suits, Michael D -- Boraston, Alisdair B -- Atherly, Todd -- Ziemer, Cherie J -- Williams, Spencer J -- Davies, Gideon J -- Abbott, D Wade -- Martens, Eric C -- Gilbert, Harry J -- 097907/Wellcome Trust/United Kingdom -- BB/G016127/1/Biotechnology and Biological Sciences Research Council/United Kingdom -- GM090080/GM/NIGMS NIH HHS/ -- MOP-68913/Canadian Institutes of Health Research/Canada -- WT097907AIA/Wellcome Trust/United Kingdom -- England -- Nature. 2015 Jan 8;517(7533):165-9. doi: 10.1038/nature13995.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉1] Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle-upon-Tyne NE2 4HH, UK [2] Complex Carbohydrate Research Center, The University of Georgia, 315 Riverbend Road, Athens, Georgia 30602, USA. ; Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle-upon-Tyne NE2 4HH, UK. ; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan 48109 USA. ; Department of Chemistry, University of York, York YO10 5DD, UK. ; School of Chemistry and Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010, Australia. ; Interdisciplinary Biochemistry Graduate Program, Indiana University, 800 E. Kirkwood Avenue, Bloomington, Indiana 47405, USA. ; Department of Chemistry, Indiana University, 800 E. Kirkwood Avenue, Bloomington, Indiana 47405, USA. ; Department of Pharmaceutical Chemistry, University of Kansas School of Pharmacy, 2095 Constant Avenue, Lawrence, Kansas 66047, USA. ; Oxyrane, 9052 Ghent, Belgium. ; Complex Carbohydrate Research Center, The University of Georgia, 315 Riverbend Road, Athens, Georgia 30602, USA. ; Agriculture and Agri-Food Canada, Lethbridge Research Centre, Lethbridge, Alberta T1J 4B1, Canada. ; Biochemistry and Microbiology, University of Victoria, Victoria, British Columbia V8P 5C2, Canada. ; USDA, Agricultural Research Service, National Laboratory for Agriculture and the Environment, Ames, Iowa 50011, USA. ; 1] Complex Carbohydrate Research Center, The University of Georgia, 315 Riverbend Road, Athens, Georgia 30602, USA [2] Agriculture and Agri-Food Canada, Lethbridge Research Centre, Lethbridge, Alberta T1J 4B1, Canada.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25567280" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Bacteroidetes/cytology/enzymology/genetics/*metabolism ; Biological Evolution ; Carbohydrate Conformation ; Diet ; Enzymes/genetics/metabolism ; Female ; Gastrointestinal Tract/*microbiology ; Genetic Loci/genetics ; Germ-Free Life ; Glycoproteins/chemistry/metabolism ; Humans ; Male ; Mannans/chemistry/*metabolism ; Mannose/metabolism ; Mice ; *Models, Biological ; Models, Molecular ; Oligosaccharides/chemistry/metabolism ; Periplasm/enzymology ; Yeasts/*chemistry
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 5
    Publication Date: 2019-11-05
    Description: Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 20402069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between 9% and 39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN74379 , Agronomy (e-ISSN 2073-4395); 9; 10; 639
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  • 6
    Publication Date: 2019-07-12
    Description: This chapter describes methods developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) to implement a transdisciplinary, systems-based approach for regional-scale (local to national) integrated assessment of agricultural systems under future climate, biophysical, and socio-economic conditions. These methods were used by the AgMIP regional research teams in Sub-Saharan Africa and South Asia to implement the analyses reported in their respective chapters of this book. Additional technical details are provided in Appendix 1.The principal goal that motivates AgMIP's regional integrated assessment (RIA) methodology is to provide scientifically rigorous information needed to support improved decision-making by various stakeholders, ranging from local to national and international non-governmental and governmental organizations.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN22637
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  • 7
    Publication Date: 2019-12-13
    Description: Efforts to limit global warming to below 2C in relation to the preindustrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming 〉2C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0C warming above the preindustrial period) on global wheat production and local yield variability. A multicrop and multiclimate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by 2.3% to 7.0% under the 1.5C scenario and 2.4% to 10.5% under the 2.0C scenario, compared to a baseline of 19802010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield interannual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producerIndia, which supplies more than 14% of global wheat. The projected global impact of warming 〈2C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN64346 , Global Change Biology (ISSN 1354-1013) (e-ISSN 1365-2486); 25; 4; 1428-1444
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  • 8
    Publication Date: 2019-07-13
    Description: Current rates of agricultural water use are unsustainable in many regions, creating an urgent need to identify improved irrigation strategies for water limited areas. Crop models can be used to quantify plant water requirements, predict the impact of water shortages on yield, and calculate water productivity (WP) to link water availability and crop yields for economic analyses. Many simulations of crop growth and development, especially in regional and global assessments, rely on automatic irrigation algorithms to estimate irrigation dates and amounts. However, these algorithms are not well suited for water limited regions because they have simplistic irrigation rules, such as a single soil-moisture based threshold, and assume unlimited water. To address this constraint, a new modeling framework to simulate agricultural production in water limited areas was developed. The framework consists of a new automatic irrigation algorithm for the simulation of growth stage based deficit irrigation under limited seasonal water availability; and optimization of growth stage specific parameters. The new automatic irrigation algorithm was used to simulate maize and soybean in Gainesville, Florida, and first used to evaluate the sensitivity of maize and soybean simulations to irrigation at different growth stages and then to test the hypothesis that water productivity calculated using simplistic irrigation rules underestimates WP. In the first experiment, the effect of irrigating at specific growth stages on yield and irrigation water use efficiency (IWUE) in maize and soybean was evaluated. In the reproductive stages, IWUE tended to be higher than in the vegetative stages (e.g. IWUE was 18% higher than the well watered treatment when irrigating only during R3 in soybean), and when rainfall events were less frequent. In the second experiment, water productivity (WP) was significantly greater with optimized irrigation schedules compared to non-optimized irrigation schedules in water restricted scenarios. For example, the mean WP across 38 years of maize production was 1.1 kg/cu m for non-optimized irrigation schedules with 50 mm of seasonal available water and 2.1 kg/cu m optimized ion schedules, a 91% improvement in WP with optimized irrigation schedules. The framework described in this work could be used to estimate WP for regional to global assessments, as well as derive location specific irrigation guidance.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN44930 , Agricultural and Forest Meteorology (ISSN 0168-1923); 243; 84-92
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  • 9
    Publication Date: 2019-11-27
    Description: Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32multimodel ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most lowrainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures (and also considering changes in CO2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by 1.1 percentage points, representing a relative change of 8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN64355 , Global Change Biology (ISSN 1354-1013) (e-ISSN 1365-2486); 25; 1; 155-173
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  • 10
    Publication Date: 2019-11-23
    Description: This study presents results of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments (CGRA) of +1.5 and +2.0 C global warming above pre-industrial conditions. This first CGRA application provides multi-discipline, multi-scale, and multi-model perspectives to elucidate major challenges for the agricultural sector caused by direct biophysical impacts of climate changes as well as ramifications of associated mitigation strategies. Agriculture in both target climate stabilizations is characterized by differential impacts across regions and farming systems, with tropical maize (Zea mays) experiencing the largest losses while soy (Glycine max) mostly benefits. The result is upward pressure on prices and area expansion for maize and wheat (Triticum), while soy prices and area decline (results for rice, Oryza sativa, are mixed). An example global mitigation strategy encouraging bioenergy expansion is more disruptive to land use and crop prices than the climate change impacts alone, even in the +2.0 C World which has a larger climate signal and lower mitigation requirement than the +1.5 C World. Coordinated assessments reveal that direct biophysical and economic impacts can be substantially larger for regional farming systems than global production changes. Regional farmers can buffer negative effects or take advantage of new opportunities via mitigation incentives and farm management technologies. Primary uncertainties in the CGRA framework include the extent of CO2 benefits for diverse agricultural systems in crop models, as simulations without CO2 benefits show widespread production losses that raise prices and expand agricultural area
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN56621 , Climate Research (ISSN 0936-577X) (e-ISSN 1616-1572); 76; 1; 17-39
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